QUANTITATIVE RESEARCH METHODS

Quantitative Research Methods

Quantitative Research Methods

Introduction

The purpose of this report is to analyse the data collected from the 30 customers of a retail bank. The data is analysed using SPSS and different statistical techniques are applied to answer the questions given.

Does the preference towards banks between males and females exist?

In the first question we will be analyzing the difference between the male and female respondents opinion towards the preference towards the banks. The chi-square test is utilized to see whether there exists the significant difference between the responses.

From the cross-tabulation table it can be seen that the majority of the respondents preferred the bank among which 4 were males and 2 were females whereas the 5 respondents were undecided about the preference towards the bank.

Cross-tabulation

Count

V7

Total

male

female

V1

not at all preferred

3

1

4

not preferred

2

2

4

somewhat not preferred

1

3

4

undecided

2

3

5

somewhat preferred

1

3

4

preferred

4

2

6

highly preferred

2

1

3

Total

15

15

30

Ho: There exist no difference between the male and female respondents towards the bank preference.

H1: There exist significant difference between the male and female respondents towards the bank preference.

The chi-square test was performed to see whether the difference between the opinions of males and females exist towards the bank preference. Since the p-value is greater than the .05 (p=.65 > .05) so it can be said that no difference exist between the opinions of males and females towards the bank preference.

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

4.200a

6

.650

Likelihood Ratio

4.360

6

.628

Linear-by-Linear Association

.009

1

.926

N of Valid Cases

30

a. 14 cells (100.0%) have expected count less than 5. The minimum expected count is 1.50.

Different family life cycle stages and quality of service

To see whether the difference exist between the family life cycles stages and quality of service ANOVA was performed between the family life cycle stage and quality of service. One way ANOVA is a statistical technique that is used to compare the means of more than two groups. One way ANOVA is a part of the ANOVA family. When we are comparing the means of more than two populations based on a single treatment factor, then it said to be one way ANOVA.

Ho: There exist no difference between the family life cycle stages and importance attached to the quality of service.

H1: There exist difference between the family life cycle stages and importance attached to the quality of service.

From the table given below it can be seen that the p-value is less than .05 therefore null hypothesis is rejected and thus it can be concluded that there exist difference between the family life cycle stages and importance attached to the quality of service.

ANOVA

V6

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

9.633

1

9.633

4.875

.036

Within Groups

55.333

28

1.976

Total

64.967

29

Does the mean importance of interior décor of the bank exceed 4

One sample T-test was performed to see whether the mean importance of interior décor exceed 4. The Independent-Samples T Test procedure tests the significance of the difference between two sample means.

A confidence interval for the difference between the two variables (95%). The Descriptives table displays the sample size, mean, standard deviation, and standard error for both groups.

One-Sample Statistics

N

Mean

Std. Deviation

Std. Error ...