DATA ANALYSIS

Data Analysis & Findings

Data Analysis & Findings

Frequency Distribution

A frequency distribution shows the number of observations falling into each of several ranges of values. Frequency distributions are portrayed as frequency tables, histograms, or polygons.

Frequency distributions can show either the actual number of observations falling in each range or the percentage of observations(Finn, 2007). In the latter instance, the distribution is called a relative frequency distribution.

SPSS OUTPUT: Frequencies (for DV)

Demrep

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

921

32.7

57.4

57.4



2.00

684

24.3

42.6

100.0



Total

1605

57.0

100.0



Missing

System

1212

43.0



Total

2817

100.0



Statistics

demrep

N

Valid

1605



Missing

1212

Mean

1.4262

Median

1.0000

Mode

1.00

Range

1.00

relig3

N

Valid

2263



Missing

554

Mean

1.3557

Median

1.0000

Mode

1.00

Range

2.00

Table 1. Descriptive Statistics for Independent and Dependent Variables

IV

Freqs (n)

%

Mean

Mode

Median

Range

IV1 Gender

Men

606

43.2

Women

798

66.8

IV2 Religion

1.35

1.0

1

2 (1-3)

Protestant

1521

54.0

Catholic

679

24.1

Jewish

63

2.2

Dependent

Variable

Political Party ID

1.4

1.0

1

1 (1-2)

Democrat

921

57.4

Republican

684

42.6

From above tables we observed that frequency of attend

Service is greater than offer pray; similarly the mean of democrat is slightly greater than the mean of religion while Median, Mode and Range are same for both variables.

Correlation

The correlation between two variables reflects the degree to which the variables are related. The most common measure of correlation is the Pearson Product Moment Correlation (called Pearson's correlation for short). When measured in a population the Pearson Product Moment correlation is designated by the Greek letter rho (?) (Fienberg, 2007). When computed in a sample, it is designated by the letter "r" and is sometimes called "Pearson's r." Pearson's correlation reflects the degree of linear relationship between two variables. It ranges from +1 to -1. A correlation of +1 means that there is a perfect positive linear relationship between variables. The scatterplot shown on this page depicts such a relationship(Carroll, 2007). It is a positive relationship because high scores on the X-axis are associated with high scores on the Y-axis.

Correlation matrix (my demo template assumes 3 variables in the study):

You only need to fill in one half of the matrix since each side is a mirror image.

SPSS OUTPUTCorrelations



edu5

demrep

income5

edu5

Pearson Correlation

1

.130(**)

.334(**)



Sig. (2-tailed)



.000

.000



N

2808

1602

2678

demrep

Pearson Correlation

.130(**)

1

.188(**)



Sig. (2-tailed)

.000



.000



N

1602

1605

1534

income5

Pearson Correlation

.334(**)

.188(**)

1



Sig. (2-tailed)

.000

.000



N

2678

1534

2685

** Correlation is significant at the 0.01 level (2-tailed).

Table 2. Correlation Matrix of all Study Variables

Education

Income

Political ID

Education

1

Income

.334(**)

1

Political ID

.130(**)

.188(**)

1

**=difference significant

For correlations: State which are significant and, of those the direction of correlation (positive or negative). E.g., Education and political party identity are positively and significantly correlated.

This is the main matrix of the Pearson's output. Variables have been arranged in a matrix such that where their columns/rows intersect there are numbers that tell about the statistical interaction between the variables(Benzécri, 2006). Three pieces of information are provided in each cell -- the Pearson correlation, ...