Statistics of Online Shopping

This study focuses on how customers use online shopping websites and explores the relationship between time spent on the site and money spent. The study also examines the relationship between age and shopping expenditure. The sample was selected using equal probability sampling method and the data was analyzed using SPSS software. The findings show no significant relationship between time spent and money spent, but a significant relationship between age and shopping expenditure.

Statistics
Online shopping
Student name:
Tutor name:
1 | P a g e

Statistics
Abstract
The essential focus of this study was to discover how customers were using online shopping
webpage page. The specific objectives were to check whether there was connection between time
spent on the site page and the money spent in dollars to do shopping. The investigation also
endeavored to set up if age was related to the money spent shopping. In choosing the members to
form the sample, the study used equal probability sampling method to pick the members. This
was suitable as it gave every individual from the populace equal plausibility of being picked into
the sample. The investigation used the analysis software SPSS to analyze the data collected.
Distinct estimations, for instance, mean, median, standard deviation and variance were used to
depict the data. Inferential measurements, for instance, Pearson correlation were used to
determine the amount of relationship that existed between different variables. The exploration
discoveries were displayed in tables. It was found that there was no relationship between time
spent on site page and amount of money spent in dollars on shopping. No basic relationship was
moreover found among attitude and amount spent on shopping. Regardless, there was a critical
relationship among age and proportion of money spent shopping in dollars. At long last, it was
furthermore found that there was no huge distinction in attitude between the sexes.
2 | P a g e

Statistics
Introduction
The essential focus of this study was to determine how customers were using online shopping
webpage page. The specific objectives were to establish whether there was correlation between
time spent on the site page and the money spent in dollars to do shopping. The investigation also
attempted to find out if age was related to the aggregate amount spent shopping.
Sampling
In order to choose a sample that did not promote biasness, the study employed two sampling
methods. The main system to be utilized was purposive inspecting then the second procedure
was equal probability sampling method. Purposive sampling was utilized to pick a pool of
respondents who have reliably visited the site page for web shopping. This was done to ensure
that the overall public who had not visited the site page does not get into the sample. After a pool
of respondents had been picked, the study utilized the random sampling to pick an example of 50
respondents. This procedure was held onto as it empowered every part in the pool to have an
equivalent chance of being picked in the sample (Hicks, 2013). It was method was less complex
on the exploration group since it required less time and resources for encourage the system
(Fleiss and Paik, 2003). This turned out to be helpful as there was restriction of time.
Methodology
This research used the statistical package for social sciences, SPSS for analysis of the data
collected. Various estimations, for instance, mean, median, standard deviation and variance were
used to depict the data. Inferential statistics, for instance, Pearson test for correlation was used to
determine the extent of relationship between different variables (Bhattacharyya and Johnson,
2013). The analysis discoveries were displayed in tables.
3 | P a g e

Statistics
NO. 1
a. Hypothesis
H0: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
H1: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
b. Hypothesis
H0: There exists no difference in mean attitude between the males and females.
H1: There exists a significant difference in mean attitude between the males and females.
This is a two tailed test.
c. Hypothesis
H0: There exist no relationship between attitude and sum amount spent shopping on the site in
dollars.
H1: There exist a significant relationship between attitude and sum amount spent shopping on the
site in dollars.
d. Hypothesis
H0: There exist no relationship between age and sum amount spent shopping on the site in
dollars.
H1: There exist a significant relationship between age and sum amount spent shopping on the site
in dollars.
4 | P a g e

Statistics
NO. 2
DESCRIPTIVE STATISTICS
Statistics
Age Attitude Time Amount spent
N Valid 50 50 50 50
Missing 0 0 0 0
Mean 34.5200 5.5800 10.3980 7.2406
Median 35.0000 6.0000 8.1000 7.1200
Std. Deviation 13.3817 1.85263 11.2562 3.28252
Variance 179.071 3.432 126.704 10.775
Minimum 16.00 2.00 .70 .00
Maximum 63.00 9.00 62.00 21.32
Table 1
NO. 3
Different test statistics
a. Hypothesis
H0: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
H1: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
Since it is a test of relationship/correlation, Pearson correlation is appropriate.
b. Hypothesis
H0: There exists no difference in mean attitude between the males and females.
H1: There exists a significant difference in mean attitude between the males and females.
Since it is a test for difference in mean, independent sample t-test is appropriate.
5 | P a g e

Statistics
c. Hypothesis
H0: There exist no relationship between attitude and sum amount spent shopping on the site in
dollars.
H1: There exist a significant relationship between attitude and sum amount spent shopping on the
site in dollars.
Since it is a test of correlation, Pearson correlation is appropriate.
d. Hypothesis
H0: Age is not related to amount of money spent by customers on shopping.
H1: Age is significantly related to amount of money spent by customers on shopping.
Since it is a test of relationship, Pearson correlation is appropriate.
NO. 4
a. Hypothesis
H0: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
H1: There exist no relationship between amount of time in minutes taken on shopping webpage
and sum amount spent shopping on the site in dollars.
Correlations
Time Amount spent
Time Pearson Correlation 1 -.071
Sig. (2-tailed) .626
N 50 50
Amount spent Pearson Correlation -.071 1
Sig. (2-tailed) .626
N 50 50
Table 2
6 | P a g e

Statistics
It was established by computation that the Pearson correlation coefficient r was - 0.07 showing a
feeble relationship. The relationship was negative and as well not significant (p=0.63) (Dixon
and Massey, 2009).
b. Hypothesis
H0: There exists no difference in mean attitude between the males and females.
H1: There exists a significant difference in mean attitude between the males and females.
Table of results
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed)
Mean
Difference
Std. Error
Differenc
e
95% Confidence Interval
of the Difference
Lower Upper
Attitud
e
Equal variances
assumed
1.18
6
.282 1.6
30
48 .110 .84000 .51536 -.19621 1.87621
Equal variances
not assumed
1.6
30
46.
990
.110 .84000 .51536 -.19678 1.87678
Table 3
It was established by computation that the P-value was 0.28 which is greater than the set alpha at
0.05. The decision is, we fail to reject the null hypothesis. We conclude that there exists no
difference in mean attitude between the males and females
c. Hypothesis
H0: There exist no relationship between attitude and sum amount spent shopping on the site in
dollars.
H1: There exist a significant relationship between attitude and sum amount spent shopping on the
site in dollars.
7 | P a g e

Statistics
Correlations
Amount spent Attitude
Amount spent Pearson Correlation 1 -.021
Sig. (2-tailed) .887
N 50 50
Attitude Pearson Correlation -.021 1
Sig. (2-tailed) .887
N 50 50
Table 4
It was established by computation that the Pearson correlation coefficient r was - 0.02 showing a
feeble relationship. The relationship was negative and as well not significant (p=0.89)
d. Hypothesis
H0: Age is not related to amount of money spent by customers on shopping.
H1: Age is significantly related to amount of money spent by customers on shopping
Table of results
Correlations
Amount spent Age
Amount spent Pearson Correlation 1 .433**
Sig. (2-tailed) .002
N 50 50
Age Pearson Correlation .433** 1
Sig. (2-tailed) .002
N 50 50
**. Correlation is significant at the 0.01 level (2-tailed).
Table 5
It was established by computation that the Pearson correlation coefficient r was 0.443 showing a
strong relationship. The relationship was positive and as well significant (p=0.002).
8 | P a g e

Statistics
References
Statistics for Management and Economics, Duxbury Press, Belmont, CA. (n.d.).
Bhattacharyya, G. K., & Johnson , R. A. (2013). Statistical Concepts and Methods. New York:
John Wiley and Sons.
Dixon , W. J., & Massey, F. J. (2009). Introduction to Statistical Analysis. New York: McGraw-
Hill.
Hicks, C. R. (2013). Fundamental Concepts in the Design of Experiments. New-York: Rhinehart
and Winston.
9 | P a g e