The COMM 291 is a paired End Term project done as a group about how gender affects clothes purchase to obtain primary data. The survey was completed by 30 respondents, and data was collected analyzed to evaluate how gender influences the consumption of clothes. The data collected is also visualized to display the data collected in table form.
Responses
Link: https://docs.google.com/forms/d/1nHuQNAEXbeyfDISjTzmslE4r3plWwz82bRV_HuntGM/edit
Numerical Descriptive Measure for Numerical Variables
| The number of Application Respondents has bought clothes in the last three months. | |
| Mean | 70.5 |
| Median | 70.5 |
| Range | 29 |
| Variance | 77.5 |
| Standard Deviation | 8.66 |
| Coefficient of Variation | 43.36% |
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Explanation of the results
Mean
The mean is the most significant measure of the central tendency. It represents the averages of data collected from the survey. The mean of this survey shows the number of applications respondents have bought clothes in the last three months. In the table above, 70.5 is the mean of respondents who have bought clothes in the last three months. The value is the average of the score from 30 respondents.
Median
Median is a measure of a tendency that separates the highest half and the lowest half of the data set. It divides the data set into two halves. It is the middle value of a data set. The median of data collected from this survey is 70.5, representing the middle figure of the data set of those who have bought clothes in the last three months.
Range
Range measures the variation between the data set. It represents the dispersion of those who have bought clothes in the last three months. The range is the difference between the smallest and largest values of the data set. The range of this data set is 29.
Variance and Standard Deviation
These are other methods of measuring the variation of the data set. The variance and standard deviation are 77.5 and 8.66, respectively. A higher value of standard deviation infers that the data set has higher variations from the mean.
Coefficient of Variation
Another important method of measuring variation is the coefficient of variation. It measures the variation of the data set relative to the mean. The coefficient of variation of the number of respondents who have bought clothes in the last three months is 43.36%.
Number of Application Respondents frequently buy new clothes |
|
| Mean | 102.00 |
| Median | 82.82 |
| Range | 349.98 |
| Variance | 2,069.65 |
| Standard Deviation | 45.49 |
| Coefficient of Variation | 44.6% |
Interpretation and Analysis
This part discusses the frequency of how respondents buy new clothes.
Mean
The mean is the averages of the data about how frequently respondents buy clothing. When answering this question, responses obtained from respondents differed based on gender. Women had positive responses than men. The mean for this data set is 102.00.
Median
The data set's median represents the median value of the data set of how frequent respondents buy new clothes. The median of the data set for how frequent respondents buy new clothing. The median value of this data set is 82.82.
Range
Range measures the variation between the data set. It represents the dispersion of the frequency of how respondents buy new clothes. It is the difference between the smallest and largest values of the data set. The range of this data set is 349.98. This data set range is relatively high, which infers that the many respondents participated in the survey.
Variance and Standard Deviation
The variance measures the degree of variation within the values in the data set. The variance of this data set is relatively high, 2,069.65. The value infers that responses from respondents had a wide difference. The standard deviation of the data set shows how values deviate from the mean. The standard deviation for this data set is 45.49. The value is relatively low, which means the values in the data set moderately from the mean.
|
The number of application respondents has bought clothes in the last three months, and the Number of application respondents frequently buy new clothes. |
|
| Covariance | 635.50 |
| Coefficient of Correlation | 0.500 |
Interpretation and Explanations
Covariance
The covariance is a measure of linear association between two data sets. It is the mean value of the product of the deviation of two data sets. In case the covariance is high, it infers the deviation of each data set's value is relatively high. The covariance between the number of application respondents who have bought clothes in the last three months and many application respondents who frequently buy new clothes is 635.50. The values of the covariance mean the variation of the two data sets moves in the same direction. Therefore, results mean the linear relationship between the two numerical variables is direct.
Coefficient of Correlation
The coefficient of correlation evaluates the level strength of a linear relationship between two numerical data sets. The value ranges between -1 and 1. A high positive value of the correlation coefficient illustrates that the linear relationship between the two sets is strong. In comparison, a negative value shows a weak linear relationship between the two sets. The coefficient of correlation between the number of application respondents who have bought clothes in the last three months and the number of application respondents who frequently buy new clothes is 0.5. A positive value means a direct linear correlation between the deviations between the two data sets exists.
Probability
The probability illustrates how different gender consume new clothes. The table below shows the distribution of consumption per gender.
Contingency table for gender and new clothes brands |
|||||
| Respondents |
Jade collection |
Kings collections |
Tasha Apparel |
Style pick |
Total |
| Male |
5 |
3 |
2 |
1 |
11 |
| Female |
25 |
23 |
20 |
5 |
73 |
| Total |
28 |
26 |
22 |
6 |
84 |
Contingency table for gender and new clothes brands |
|||||
| Respondents |
Jade collection |
Kings collections |
Tasha Apparel |
Style pick |
Total |
| Male |
16.67% |
10% |
6.67% |
3.33% |
13.10% |
| Female |
83.33% |
76.67% |
66.67% |
16.67% |
86.9% |
| Total |
100% |
86.67% | 73.3% |
20% |
100% |
Calculation and Explanation
Jade collection Male = 16.67%
Jade collection female = 83.33%
Kings Collection Male = 10%
Kings Collection female = 76.67%
Tasha apparel male = 6.67%
Tasha apparel female = 66.67%
Stylepick male = 3.33%
Stylepick female = 16.67%
The first contingency table contains the consumption of new brands of clothes per gender. According to the table's data, the female gender consumes the new Jade collection's new clothing than male consumers. The second contingency table shows the percentage consumption of new clothes per gender. The brands consumed by both genders differ.
New Clothes Consumption per Gender
Contingency table for gender and new clothes brands |
|||||
| Respondents |
Jade collection |
Kings collections |
Tasha Apparel |
Style pick |
Total |
| Male |
16.67% |
10% |
6.67% |
3.33% |
13.10% |
| Female |
83.33% |
76.67% |
66.67% |
16.67% |
86.9% |
| Total |
100% |
86.67% | 73.3% |
20% |
100% |
