CHAPTER 7 DESCRIPTIVE ANALYSIS

7.0 Chapter Overview This chapter presents a descriptive analysis of the data obtained through data collection instruments. The data were analyzed descriptively in terms of measures of central tendency and measures of variability. A measure of central tendency includes the mean, median and mode. A measure of variability includes standard deviation, skewness and kurtosis. Descriptive analysis of data is necessary as it helps to determine the normality of the distribution. The nature of the statistical technique to be applied for inferential analysis of the data depends on the characteristics of the data.

7.1 Introduction Research consists of systematic observation and description of the characteristics or properties of objects or events for the purpose of discovering relationships between variables. The ultimate purpose is to develop generalizations that may be used to explain phenomena and to predict future occurrences. To conduct research, principles must be established so that the observation and description have a commonly understood meaning. Measurement is the most precise and universally accepted process of description, assigning quantitative values to the properties of objects and events.(Best, 1981). Planning and care in research design and data collection provides a substantial guarantee of quality in research but the ultimate test lies in the analysis (Best J. W., 1981). Data in the real world often comes with a large quantum and in a variety of formats that any meaningful interpretation of data cannot be achieved straightway. In order to achieve the objectives of the study, analysis of the data collected forms an important and integral part. Analysis means categorizing, classifying and summarizing data to obtain answers to the research questions. Classification also helps to reduce the vast data into intelligible and interpretable forms (Youngman, 1979).

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In order to do statistical analysis, two types of data are recognized these are 1. Parametric data: Data of this type are measured data, and parametric statistical tests assume that the data are normally or nearly normally distributed. Parametric tests are applied to both interval and ratio scaled data. 2. Non Parametric data: data of this type are either counted or ranked non parametric tests, sometimes known as distribution free tests, do not rest upon the more stringent assumption of normally distributed populations

Two types of statistical application are used for generalization. These are descriptive statistical analysis and inferential statistical analysis. The present chapter discusses the descriptive data analysis used by the researcher for her study.

7.2 Descriptive Data Analysis Descriptive analysis of data limits generalization to a particular group of individuals observed. No conclusions extend beyond this group and any similarity to those outside the group cannot be assumed. The data describe one group and that group only. Much simple action research involves descriptive analysis and provides valuable information about the nature of the particular group of individuals (Best & Kahn, 2003). The descriptive analysis of data provides the following: 

The first estimates and summaries, arranged in tables and graphs, to meet the objectives.



Information about the variability or uncertainty in the data



Indications of unexpected patterns and observations that need to be considered when doing formal analysis

Descriptive analysis is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Together with simple graphical analysis, they form the basic virtual of any quantitative analysis of data. With descriptive analysis, one simply describes what is or what the data shows. Description of data is needed to determine the normality of the distribution, description of the data is necessary as the nature of the techniques to be applied for inferential analysis of the data depends on the characteristics of the data

194

7.3 Procedure of Descriptive Analysis Once the data are grouped, different statistical measures are used to analyze data and draw conclusions. For the present study, the following statistical measures of descriptive analysis were used to compute further statistical testing. 1. Measures of Central tendency. 2. Measures of Variability. 3. Measures of Divergence from Normality. 4. Measures of Probability. Graphical methods have been adopted for translating numerical facts into more concrete and understandable form.

7.3.1 Measures of central tendency The central tendency of a distribution is an estimate of the “center” of a distribution value. There are three major types of measures of central tendency Mean The Mean or average is probably the most commonly used methods of describing a central tendency. The mean represents the center of gravity of distribution. Each score in a distribution contributes to the determination of mean. It is also known as arithmetic average. Mean is the average of all values in a distribution (Krishnaswamy & Ranganathan, 2006). To compute the mean, all the values are added and divided by the total number of values. It is the ratio of summation of all scores to the total numbers of scores. Using mean one can compare different groups. It also helps in computing further statistics. Since this method involves handling of large numbers and entails tedious calculations, the researcher used data analysis tools available in a simple Microsoft® office suite, Excel 2007 to calculate the mean. The mode of function is Formulas/More functions/Statistical/ Average. The mean is calculated as: AVERAGE (number1, number2…) Where, Average= mean (number1, number2…) = range of scores

195

Mean can also be calculated using the formula:∑

x= Where, x = sample mean ∑ fx = sum of scores in a distribution N = number of items

Median The median is the positional average that divides a distribution into two equal parts so that one half of items falls above it and the other half below it. In other words, the midpoint of a distribution of values is called the median. It is the point, below and above which 50% of the population lies. The Median is the score found in the exact middle of the set of values. One way to compute the median is to list all scores in numerical order, and then locate the scores in the center of the sample. If there is an even number of numbers in the set, then the median calculates the average of the two numbers in the middle. Median =

⌈

⌉

Where, l = lower limit of median class. N = number of scores in a series. fm = frequency of median class c = length of class interval F= no, of cases below the median. The researcher used data analysis tools available in the simple Microsoft® office suite, Excel 2007 to calculate the median. The mode of function is Formulas/More functions/Statistical/ Median.

Mode The mode is the most frequently occurring value in the set of scores. The mode is indirectly calculated mean and median. It is a quick and appropriate measure of central tendency.

196

The mode can be calculated as the largest frequency in the distribution, using the following formula: Mode = 3 (median) – 2 (mean) The researcher used data analysis tools available in the simple Microsoft® office suite, Excel 2007 to calculate the mode. The mode of function is Formulas/More functions/Statistical/ Mode.

7.3.2. Measures of variability The measures of central tendency indicate the central value of the distribution. However, the central value alone is not sufficient to fully describe the distribution. (Kaul, 2007). In addition to the measures of centrality, we require a measure of the spread of the actual scores. The extent of such spread may vary from one distribution to another. The extent of such variability is measured by the measures of variability. Variability describes the way the classes are distributed and how they are changing in relation to a variety. For example, Range and Standard Deviation. The technique employed in the present study is Standard Deviation. The range is simply the highest value minus the lowest value. The standard deviation is more accurate and detail measure of dispersion.

Standard Deviation The standard deviation shows the relation that set of scores has with the mean of the sample. Standard deviation is expressed as the positive square root of the sum of the squared deviations from the mean divided by the number of scores minus one. It is the average difference between observed values and the mean. The standard deviation is used when expressing dispersion in the same unit as the original measurement. It is designated as (σ) The standard deviation can be calculated using the following formula: σ = i√Σfx2-c2 N Where,

σ = Standard Deviation (S.D.) i = length of class interval Σ = sum of x2= squares of the deviations of scores from the assumed mean 197

f = frequency of class interval c2 = square of correction N = total number of scores

The researcher used data analysis tools available in the simple Microsoft® office suite, Excel 2007 to calculate the S.D. The mode of function is Formulas/More functions/Statistical/ STDEV.

7.3.3. Measure of Divergence from Normality An important aspect of the “description” of a variable is the shape of its distribution, which tells the frequency of values from different range of variables. A researcher is interested in how well the distribution can be approximated from the normal distribution. Simple description statistic can provide some information relevant to this issue. The two measures used to determine the shape of distributions are skewness and kurtosis. Skewness: Many times it is seen that the mean, median and mode of the distribution don’t fall at the same place, i.e. the scores may extend much farther in one direction than the other. Such a distribution is called a skewed distribution. Positively skewed distribution: The distribution is positively skewed when most of the scores pile up at the low end (or left) of the distribution and spreads out more gradually towards the high end of it. In a positively skewed distribution, the mean falls on the right side of the median. Negatively skewed distribution: The distribution is negatively skewed if the scores are concentrated towards the upper value and it is positively skewed if they cluster towards lower value. The mean of the distribution is higher than the median in positive skewness whereas the median value is greater than the mean in negative skewness. Skewness = Mean - Mode SD For the present study skewness was calculated using Microsoft Excel 2007.The mode of function is Formulas/More functions/Statistical/ SKEW.

198

Kurtosis The term “Kurtosis “refers to “peakedness ” or the flatness of a frequency distribution as compared with the normal. A frequency distribution more peaked than the normal is said to be Leptokurtic and a frequency distribution flatter than the normal is called Platykurtic. A normal curve is also termed as Mesokurtic. Positive kurtosis indicates a relatively peaked distribution leptokurtic and negative kurtosis indicates a relatively flat distribution, which is platykurtic. The researcher used data analysis tools available in the simple Microsoft® office suite, Excel 2007 to calculate the Kurtosis. The mode of function is Formulas/More functions/Statistical/ KURT.

7.3.4 Measures of Probability (fiduciary limits) In order to estimate the population mean or the probable variability, it is necessary to set up limits for a given degree of confidence which will embrace the mean or the standard deviation since limits define the confidence interval.

Estimation of Population parameters :-( Fiduciary Limits) The limits of the confidence intervals of parameters are called fiduciary limits. They are calculated for both mean and standard deviation at 0.95 and 0.99 levels of confidence. The formula used for calculating standard error of mean and fiduciary limits is:S.EM. = σ √N At 0.95 level; mean +S. EM × 1.96 At 0.99 level; mean +S. EM × 2.58 The formula used for calculating standard error of S.D.:S.ED = 0 .71σ √N At 0.95 level; S.D.+ S. ED × 1.96 At 0.99 level; S.D.+ S. ED × 2.58 Where, S. EM = standard error of mean S. ED = standard error of standard deviation σ= standard deviation 199

N= total number of scores M= Mean

7.4 Graphical Representation Aid in analyzing numerical data may often be obtained from a graphic or pictorial treatment of the frequency distribution. The advertisements have long used graphic methods because these devices catch the eye and hold the attention when the most careful array of statistical evidence fails to attract notice for this and other reasons the research worker also utilizes the attention- getting power of visual presentation; and at the same time, seeks to translate numerical facts often abstract and difficult to interpret, into more concrete and understandable form. In the present study, the researcher used graphical representation in the form of line diagrams and pie-charts.

7.5 Descriptive Statistical Analysis of data The data were obtained for the variables involved in the study from Bachelor of Education students of different B Ed colleges. The study was conducted in two phases; hence this chapter deals with the description of the variables in the two phases of the study. Phase I: This section deals with the description of the following variables: 1. Information Literacy Skills of students from Arts Faculty 2. Information Literacy Skills of students from Science Faculty 3. Information Literacy Skills of students from Commerce Faculty 4. Information Literacy Skills of students with Graduate degree 5. Information Literacy Skills of students with Post Graduate degree Phase II: This section deals with the description of the following variables: 1. Information Literacy Skills pre-test scores of control group 2. Information Literacy Skills post-test scores of control group 3. Information Literacy skills pre-test scores of experimental group 4. Information Literacy skills post-test scores of experimental group

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7.5.1: Descriptive Statistics of Information Literacy Skills of students from Arts Faculty

Table 7.1 Descriptive Statistics of Information Literacy Skills among Student Teachers from Arts Faculty Faculty

Total

Mean

Median

Mode

sample

Arts

182

Standard

Skewness

Kurtosis

-0.1575

0.033

Deviation 13.79

14

14.42

4

As evident from the Table 7.1 the value of mean, median, mode are 13.79, 14, and 14.42 respectively. The mode is higher than the mean and median. This indicates that the distribution is negatively skewed indicating high scores. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is leptokurtic in nature indicating peaked distribution. 7.5.1.1 Estimation of population parameters Table 7.2 SE and FL of Mean and Standard Deviation of the distribution of information literacy skills among the students of arts faculty Faculty

Arts

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.296

S.ED = 0.210

Fiduciary limit at

Fiduciary limit at

182

0.95

0.99

0.95

0.99

14.37

14.63 to

4.4116 to

4.5418 to 3.45

to 13.21

12.94

3.584

The standard error mean is 0.296. The fiduciary limit is at 0.95 is 14.37 to 13.21which indicates that out of 100, 95 times the population mean will lie between the ranges 14.37 to 13.21

201

The fiduciary limit of 0.99 is 14.63 to 12.94which indicates that out of 100, 99 times the population mean will lie between the ranges 14.63 to 12.94 The standard error deviation is 0.210 The fiduciary limit of 4.4116 to 3.584 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 4.4116 to 3.584 The fiduciary limit of 0.99 is 4.5418 to 3.45which indicates that out of 100, 99 times the population standard deviation will lay between 4.5418 to 3.45.

Table 7.3 Distribution of Original and Smoothed Frequencies of Information Literacy skills of students from Arts faculty is presented graphically in figure 7.1 Class interval

Original frequencies

Smoothened frequencies 2

14.333

6- 10

37

66.333

11-15

82

135.666

16-20

50

135.666

20-25

11

61

0-5

202

Figure 7.1 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills of students from Arts Faculty Frequency polygons of the original and the smoothened frequencies of information literacy skills of students from arts faculty 160

140

120

Frequencies

100

80

60

40

20

0 0-5

6-10

11-15

16-20

21-25

Class Intervals Original Frequencies

Smoothened Frequencies

203

7.5.2: Descriptive Statistics of Information Literacy Skills of students from Commerce Faculty Table 7.4 Descriptive Statistics of Information literacy skills among student teachers from Commerce Faculty Faculty

Total

Mean Median

Mode Standard

sample

Skewness

Kurtosis

-0.02

-0.677

Deviation

Commerce 107

14.29

14

13.42

3.92

As evident from the table 7.4 the value of mean, median, mode are 14.29, 14, and 13.42 respectively. This indicates that the distribution is negatively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

7.5.2.1 Estimation of population parameters

TABLE 7.5 SE and FL of mean and Standard Deviation of the distribution of information literacy skills among the students of Commerce Faculty Faculty

Commerce

Sample

S.E of mean

S.E of SD

size (N)

S.EM = 0.3868

S.ED = 0.2746

Fiduciary limit at

Fiduciary limit at

107

0.95

0.99

0.95

0.99

14.758 to

14.9979 to

4.5382 to

4.7084 to

13.2418

13.0021

3.4618

3.2916

The standard error mean is 0.3868. The fiduciary limit is at 0.95 is 14.758 to 13.2418 which indicates that out of 100, 95 times the population mean will lie between the ranges 14.758 to 13.2418 The fiduciary limit of 0.99 is 14.9979 to 13.0021which indicates that out of 100, 99 times the population mean will lie between the ranges 14.9979 to 13.0021 204

The standard error deviation is 0.2746 The fiduciary limit of 4.5382 to 3.4618which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 4.5382 to 3.4618 The fiduciary limit of 0.99 is 4.7084 to 3.2916which indicates that out of 100, 99 times the population standard deviation will lay between 4.7084 to 3.2916.

Table 7.6 Distribution of Original and Smoothened frequencies of Information literacy skills of students from Commerce Faculty is presented graphically in Figure 7.2

Class interval

Original frequencies

Smoothened frequencies

0-5

0

7

6-10

21

36

11-15

45

78

16-20

36

82.66667

21-25

5

41

205

Figure 7.2 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills of students from Commerce Faculty Frequency polygons of the original and the smoothened frequencies of information literacy skills of students from commerce faculty 90

80

70

Frequencies

60

50

40

30

20

10

0 0-5

6-10

11-15

16-20

21-25

Class Intervals Original Frequencies Smoothened Frequencies

206

7.5.3 Descriptive Statistics of Information Literacy Skills of students from Science Faculty Table 7.7 Descriptive statistics of Information literacy skills among Student teachers from Science Faculty Faculty Total

Mean

Median

Mode

Standard Skewness

sample Science

97

Kurtosis

deviation 15.44

16

16

4.033

0.06861

-0.23877

As evident from the table 7.7 the value of mean, median, mode are 15.44, 16, 16 respectively. As the scores are gradually increasing this indicates that the distribution is positively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature

7.5.3.1 Estimation of population parameters

Table 7.8 SE and FL limit of mean and Standard Deviation of the distribution of Information literacy skills among the students of Science Faculty Faculty

Science

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.4095

S.ED = 0.29076*,

Fiduciary limit at

Fiduciary limit at

97

0.95

0.99

0.95

0.99

16.24 to

16.49651 to

6.283 to

4.7812 to

14.637

14.38349

1.783

3.2848

The standard error mean is 0.4095 The fiduciary limit is at 0.95 is 16.24 to 14.637 which indicates that out of 100, 95 times the population mean will lie between the ranges 16.24 to 14.637 The fiduciary limit of 0.99 is 16.49651 to 14.38349which indicates that out of 100, 99 times the population mean will lie between the ranges 16.49651 to 14.38349 207

The standard error deviation is 0.29076 The fiduciary limit of 6.283 to 1.783which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 6.283 to 1.783 The fiduciary limit of 0.99 is 4.7812 to 3.2848which indicates that out of 100, 99 times the population standard deviation will lay between 4.7812 to 3.2848 Table 7.9 Distribution of Original and Smoothened Frequencies of Information literacy skills of students from Science Faculty is presented graphically in Figure 7.3

Class interval

Original frequencies

Smoothened frequencies 0

3.666

6- 10

11

22.333

11-15

34

58.666

16-20

41

78.666

20-25

11

52

26-30

0

11

0-5

208

Figure 7.3 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills of students from Science Faculty

Frequency polygons of the original and the smoothened frequencies of information literacy skills of students from science faculty 90

80

70

Frequencies

60

50

40

30

20

10

0 0-5

6-10

11-15

16-20

21-25

26-30

Class intervals Original Frequencies

Smoothened Frequencies

209

7.5.4: Standard Error and Fiduciary Limit of Information Literacy skills among the students of different faculty

Table 7.10 SE and FL of Mean and Standard Deviation of the distribution of Information literacy skills among the Students of Different Faculty

Faculty

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.296*,0.4095**,

S.ED =

0.3868***

0.210*,0.29076**, 0.2746***

Fiduciary limit at

Arts*

Science**

Commerce***

182

97

107

Fiduciary limit at

0.95

0.99

0.95

0.99

14.37 to

14.63 to

4.4116 to

4.541 to 3.45

13.21

12.94

3.584

16.24 to

16.49651 to

6.283 to

4.781 to

14.637

14.383

1.783

3.284

14.758 to

14.9979 to

4.538to

4.708 to

13.2418

13.002

3.461

3.291

210

7.5.5 : Descriptive Statistics of Information Literacy Skills of students with graduate degree

Table 7.11 Descriptive statistics of Information literacy skills among Student teachers with Graduate Degree Faculty

Total

Mean

Median

Mode

sample

Standard Skewness

Kurtosis

deviation

Graduate 237

14.131

14

13

4.0677

0.0985

-0.0698

As evident from the table 7.11 the value of mean, median, mode are 14.131, 14, 13 respectively. This indicates that the distribution is positively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

7.5.5.1 Estimation of population parameters

Table 7.12 SE and FL of Mean and Standard Deviation of the distribution of Information literacy skills among the students teachers with Graduate Degree Faculty

Graduate

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.2642

S.ED = 0.1876

Fiduciary limit at

Fiduciary limit at

237

0.95

0.99

0.95

0.99

14.64 to

14.80 to 13.46

4.43 to 3.70

4.55 to 3.58

13.62

The standard error mean is 0.2642 The fiduciary limit is at 0.95 is 14.64 to 13.62 which indicates that out of 100, 95 times the population mean will lie between the ranges 14.64 to 13.62

211

The fiduciary limit of 0.99 is 14.80 to 13.46 which indicates that out of 100, 99 times the population mean will lie between the ranges 14.80 to 13.46 The standard error deviation is 0.1876 The fiduciary limit of 4.43 to 3.70 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 4.43 to 3.70 The fiduciary limit of 0.99 is 44.55 to 3.58 which indicates that out of 100, 99 times the population standard deviation will lay between 4.55 to 3.58.

Table 7.13 Distribution of Original and Smoothened Frequencies of Information literacy skills of student teachers with Graduate degree is presented graphically in figure 7.4

CLASS INTERVAL

ORIGINAL

SMOOTHENED

FREQUENCIES

FREQUENCIES 2

16.333

6- 10

43

78.333

11-15

100

169

16-20

78

182.666

20-25

14

30.666

0-5

212

Figure 7.4 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills of students with Graduate degree

200

Frequency polygons of the original and the smoothened frequencies of information literacy skills of students with graduate degree

180

160

140

Frequencies

120

100

80

60

40

20

0 0-5

6-10

11-15

16-20

20-25

Class Intervals ORIGINAL FREQUENCIES

SMOOTHENED FREQUENCIES

213

7.5.6 : Descriptive Statistics of Information Literacy Skills of students with graduate degree

Table 7.14 Descriptive statistics of Information literacy skills among student teachers with Post Graduate degree Faculty

Total

Mean

Median

Mode

sample Post

Standard

Skewness

Kurtosis

-0.00813

-0.44271

Deviation

149

14.69

15

15.62

4.25

Graduate

As evident from the table 7.14 the value of mean, median, mode are 14.69, 15, 15.62 respectively. This indicates that the distribution is slightly negatively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

7.5.6.1 Estimation of population parameters

Table 7.15 SE and FL Mean and Standard Deviation of the distribution of Information literacy skills among the students’ teachers with Post Graduate Degree Faculty

Post Graduate

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.34822

S.ED = 0.2472

Fiduciary limit at

Fiduciary limit at

149

0.95

0.99

0.95

0.99

15.37 to 14

15.58 to

4.73 to 3.76

4.88 to

13.792

3.612

The standard error mean is 0.34822 The fiduciary limit is at 0.95 is 15.37 to 14which indicates that out of 100, 95 times the population mean will lie between the ranges 15.37 to 14 214

The fiduciary limit of 0.99 is 15.58 to 13.792which indicates that out of 100, 99 times the population mean will lie between the ranges 15.58 to 13.792 The standard error deviation is 0.2472 The fiduciary limit of 4.73 to 3.76which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 4.73 to 3.76 The fiduciary limit of 0.99 is 4.88 to 3.612which indicates that out of 100, 99 times the population standard deviation will lay between 4.88 to 3.612

Table 7.16 Distribution of Original and Smoothened Frequencies of Information literacy skills of students with Post Graduate Degree is presented graphically in Figure 7.4

Class interval

Original frequencies

Smoothened frequencies

0-5

0

8.666

6-10

26

46.333

11-15

61

103.333

16-20

49

114.333

21-25

13

62

0

13

26-30

215

Figure 7.5 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills of students with Post Graduate Degree

Frequency polygons of the original and the smoothened frequencies of information literacy skills of students with post graduate degree 140

120

Frequencies

100

80

60

40

20

0 0-5

6-10

11-15

16-20

21-25

26-30

Class Intervals ORIGINAL FREQUENCIES

SMOOTHENED FREQUENCIES

216

7.5.7.: Standard Error and Fiduciary Limit of Information Literacy skills among the students of different faculty

Table 7.17 SE and FL of Mean and Standard Deviation of the distribution of Information literacy skills among the Students of different Faculty Faculty

Graduate* Post graduate**

Sample

S.E of mean

S.E of SD

size(N)

S.EM =

S.ED =

0.2642*,0.34822**,

0.1876*,0.2472**,

Fiduciary limit at

Fiduciary limit at

237

149

0.95

0.99

0.95

0.99

14.64 to

14.80 to

4.43 to

4.55 to 3.58

13.62

13.46

3.70

15.37 to

15.58 to

4.73 to

14

13.792

3.76

217

4.88 to 3.612

Phase II: This section deals with the descriptive analysis of the following dependent variables: 1. Information Literacy Skills pre-test scores of control group 2. Information Literacy Skills post-test scores of control group 3. Information Literacy skills pre-test scores of experimental group 4. Information Literacy skills post-test scores of experimental group

7.5.8.: Descriptive Statistics of Information Literacy Skills pre-test scores of control group

Table 7.18 Descriptive statistics of Information literacy skills Pre-test scores of Control Group Group

Total

Mean

Median

Mode

sample Pre test 46

Standard Skewness

Kurtosis

deviation 13.239 12.5

12

2.368

0.5096

-0.88

Control

As evident from the table 7.18 value of mean, median, mode are 13.239, 12.5, 12 respectively. The mean is higher than mode and median. This indicates that the distribution is positively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

218

7.5.8.1 Estimation of population parameters Table 7.19 SE and FL of Mean and Standard Deviation of the distribution of Information literacy skills Pre-test scores among the students teachers in Control Group Group

Sample size

S.E of mean

S.E of SD

(N)

S.EM = 0.34822

S.ED = 0.2472

Fiduciary limit at

Fiduciary limit at

0.95 Pre-test

46

0.99

0.95

0.99

13.923

14.1396

2.8538

3.0075

TO

TO

TO

TO

12.554

12.338

1.882

1.728

scores of Control

The standard error mean is 0.3491 The fiduciary limit is at 0.95 is 13.923 to 12.55 which indicates that out of 100, 95 times the population mean will lie between the ranges 13.923 to 12.55. The fiduciary limit of 0.99 is 14.1396 to 12.338 which indicate that out of 100, 99 times the population mean will lie between the ranges 14.1396 to 12.338. The standard error deviation is 0.2479 The fiduciary limit of 0.95 is 2.8538 to 1.8822 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 2.8538 to 1.8822. The fiduciary limit of 0.99 is 3.0075 to 1.7285 which indicates that out of 100, 99 times the population standard deviation will lay between 3.0075 to 1.7285.

219

Table 7.20 Distribution of Original and Smoothened Frequencies of Information literacy skills among the Student Teachers in Control Group is presented graphically in Figure 7.6 Class interval

Original frequencies

Smoothened frequencies

0-5

0

1.666

6-10

5

15

11-15

30

38.666

16-20

11

41

21-25

0

11

220

Figure 7.6 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy Pre-test Scores among the student teachers in Control Group

Frequency polygons of the original and the smoothened frequencies of information literacy pre-test scores among the student teachers in control group 45

40

35

Frequencies

30

25

20

15

10

5

0 0-5

6-10

11-15

16-20

21-25

Class intervals ORIGINAL FREQUENCIES

SMOOTHENED FREQUENCIES

221

7.5.9 Descriptive Statistics of Information Literacy Skills post-test scores of control group

Table 7.21 Descriptive statistics of Information literacy skills Post-test scores of Control Group Group

Total

Mean

Median

Mode Standard

sample Post test 46

Skewness

Kurtosis

0.603

-0.44

deviation 12.978

12

12

2.185

Control

As evident from the table 7.12 value of mean, median, mode are 12.97, 12, 12 respectively. The mean is higher than mode and median. This indicates that the distribution is positively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

222

7.5.9.1 Estimation of population parameters Table 7.22 SE and FL Mean and Standard Deviation of the distribution of Information literacy skills Post-test scores among the student teachers in Control Group Group

Sample

S.E of mean

S.E of SD

size (N)

S.EM = 0.3222

S.ED = 0.2288

Fiduciary limit at

Fiduciary limit at

0.95 POST TEST

46

0.99

0.95

0.99

13.601

13.801

2.634

2.776

TO

TO

TO

TO

12.339

12.338

1.737

1.595

SCORES OF CONTROL

The standard error mean is 0.3222 The fiduciary limit is at 0.95 is 13.601 to 12.339 which indicates that out of 100, 95 times the population mean will lie between the ranges 13.601 to 12.339. The fiduciary limit of 0.99 is 13.8012 to 12.338 which indicate that out of 100, 99 times the population mean will lie between the ranges 13.8012 to 12.338. The standard error deviation is 0.2288 The fiduciary limit of 0.95 is 2.6341 to 1.7373 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 2.6341 to 1.7373. The fiduciary limit of 0.99 is 2.776 to 1.5954 which indicates that out of 100, 99 times the population standard deviation will lay between 2.776 to 1.5954.

223

Table 7.23 Distribution of Original and Smoothened Frequencies of Information Literacy skills among the student teachers in Control Group is presented graphically in Figure 7.7 Class interval

Original frequencies

Smoothened frequencies

0-5

0

2

6-10

6

17

11-15

33

41.33333

16-20

7

40

21-25

0

7

224

Figure 7.7 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills Post-test scores among the students teachers in Control Group Frequency polygons of the original and the smoothened frequencies of information literacy skills post test scores among the students teachers in control group 80

70

60

Frequencies

50

40

30

20

10

0 0 5

6 10

11 15

16-20

21- 25

Class intervals Original Frequencies

Smoothened Frequencies

225

7.5.10 Descriptive Statistics of Information Literacy Skills pre-test scores of Experimental group Table 7.24 Descriptive statistics of Information literacy skills Pre-test scores of Experimental Group Group

Total

Mean

Median Mode Standard Skewness Kurtosis

sample Pre test

65

13.661 14

19.67

3.894

-0.044

-0.7590

Experimental

As evident from the table 7.24 value of mean, median, mode are 13.661, 14, and 19.67 respectively. This indicates that the distribution is negatively skewed. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is platykurtic in nature.

7.5.9.1 Estimation of population parameters Table 7.25 SE and FL Mean and Standard Deviation of the distribution of Information literacy skills Pre-test scores among the students teachers in Experimental Group Group

Sample

S.E of mean

S.E of SD

size (N)

S.EM = 0.4830

S.ED = 0.34284

Fiduciary limit at

Fiduciary limit at

0.95 Pre test scores of

65

Experimental

0.99

0.95

0.99

14.6077

14.907

4.5659

4.778

TO

TO

TO

TO

12.714

12.414

3.222

3.01

The standard error mean is 0.4830 The fiduciary limit is at 0.95 is 14.6077 to 12.714 which indicates that out of 100, 95 times the population mean will lie between the ranges 13.601 to 12.339.

226

The fiduciary limit of 0.99 is 14.907 to 12.414 which indicate that out of 100, 99 times the population mean will lie between the ranges 14.907 to 12.414. The standard error deviation is 0.34284 The fiduciary limit of 0.95 is 4.5659 to 3.2221 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 4.5659 to 3.2221 The fiduciary limit of 0.99 is 4.778 to 3.01 which indicates that out of 100, 99 times the population standard deviation will lay between 4.778 to 3.01.

Table 7.26 Distribution of Original and Smoothened Frequencies of Information literacy skills among the student teachers in Experimental group is presented graphically in Figure 7.8

Class interval

Original frequencies

Smoothened frequencies

0-5

0

5.666

6-10

17

25.333

11-15

25

48.666

16-20

20

46

21-25

3

23

227

Figure 7.8 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills Pre-test scores among the students teachers in Experimental Group Frequency polygons of the original and the smoothened frequencies of Information literacy skills pre test scores among the students teachers in experimental group 60

50

Frequencies

40

30

20

10

0 0-5

6-10

11-15

16-20

21-25

Class Intervals ORIGINALFREQUENCIES

228

SMOOTHENED FREQUENCIES

7.5.10. Descriptive Statistics of Information Literacy Skills post-test scores of Experimental group

Table 7.27 Descriptive Statistics of Information literacy skills Post-test scores of Experimental Group Group

Total

Mean

Median

Mode

SD

Skewness

Kurtosis

17.538

18

18.924

4.534

-0.002

1.082

sample Post test

65

Experimental

As evident from the table 7.27 value of mean, median, mode are 17.5384, 18, 18.924 respectively. This indicates that the distribution is negatively skewed. Further the difference between mean, median mode is marginal indicating that the distribution is near normal. Hence it can be calculated that the selected sample is a representative of the population. The kurtosis of the sample is indicating that the distribution is leptokurtic in nature. 7.5.10.1 Estimation of population parameters

Table 7.28 SE and FL of Mean and Standard Deviation of the distribution of Information literacy skills Post-test scores among the student teachers in Experimental Group Group

Post test scores of Experimental

Sample

S.E of mean

S.E of SD

size(N)

S.EM = 0.562

S.ED = 0.3992

Fiduciary limit at

Fiduciary limit at

0.95

0.99

0.95

18.6356

18.9828

5.3166

5.5639

To

To

TO

TO

16.4404

16.0932

3.7514

3.505

65

229

0.99

The standard error mean is 0.562 The fiduciary limit is at 0.95 is 18.6356 to 16.4404 which indicates that out of 100, 95 times the population mean will lie between the ranges 18.6356 to 16.4404. The fiduciary limit of 0.99 is 18.9828 to 16.0932 which indicate that out of 100, 99 times the population mean will lie between the ranges 18.9828 to 16.0932. The standard error deviation is 0.3992 The fiduciary limit of 0.95 is 5.3166 to 3.7514 which indicates that out of 100, 95 times the population standard deviation will lie between the ranges 5.3166 to 3.7514 The fiduciary limit of 0.99 is 5.5639 to 3.505 which indicates that out of 100; 99 times the population standard deviation will lay between 5.5639 to 3.505.

Table 7.29 Distribution of Original and Smoothened Frequencies of Information literacy skills among the student teachers in Experimental Group is presented graphically in figure 7.9

Class interval

Original frequencies

Smoothened frequencies

1-10

6

20.333

11-20

43

54

21-30

15

58.333

31-40

1

16

230

Figure 7.9 Frequency Polygons of the Original and the Smoothened Frequencies of Information literacy skills Post-test scores among the students teachers in Experimental Group Frequency polygons of the original and the smoothened frequencies of information literacy skills post test scores among the students teachers in experimental group 70

60

Frequenceis

50

40

30

20

10

0 1-10

11-20

21-30

31-40

Class Intervals ORIGINAL FREQUENCIES

SMOOTHENED FREQUENCIES

7.6 Summary The results of the descriptive analysis have been tabulated and graphically presented. The chapter has discussed the descriptive statistics to support the distribution of every variable in response to the objectives of the study. This is also essential to further test the hypothesis through inferential statistical techniques. The following chapter deals with the testing of hypothesis. 231