Credit Hours on the Number of Days Consuming Alcohol among Males and Females
Introduction
Stop a student on any campus across the nation and ask them if they ever consumed alcohol. Chances are the majority will say yes without hesitation. It is a common activity among students of either sex. I am questioning if there is a difference in the amount of days a male or female consumes alcohol on the number of credit hours they are taking during that semester. I predict that students who are taking less credit hours consume the most alcohol and a higher percentage of those being of the male gender. The information below will interpret data that was found poling various Info 281 students to question my claim.
Variable Selection
The data presented was found on the Student Questionnaire Excel File gathered from 158 previously enrolled info students. Males are numbered as 0 and Females are numbered 1. First, I separated the data and ordered it smallest to largest so I could get a more organized look at the data. I then put the data into a chart like this so I could show you without taking up too much room. This data is only for males though but it gives you an idea of how the information is presented. Underneath the data box is an average based on each of the number of credit hours.
10 / 12 / 13 / 14 / 15 / 16 / 17 / 18 / 19 / 203 / 0 / 0 / 0 / 0 / 0 / 0 / 0 / 2 / 1
1 / 0 / 0 / 0 / 1 / 0 / 0 / 3
1 / 1 / 0 / 0 / 1 / 1 / 0
1 / 1 / 0 / 2 / 1 / 1 / 2
1 / 2 / 1 / 2 / 1 / 1 / 4
1 / 2 / 1 / 2 / 1 / 1
1 / 2 / 1 / 2 / 2 / 1
2 / 2 / 2 / 3 / 2 / 2
2 / 2 / 3 / 3 / 2 / 2
2 / 2 / 3 / 4 / 2 / 2
2 / 2 / 3 / 4 / 2 / 2
2 / 3 / 3 / 4 / 2 / 2
3 / 3 / 3 / 7 / 2 / 2
5 / 4 / 2 / 2
5 / 2 / 3
3 / 3
3 / 3
3 / 5
3 / 6
3
4
7
3 / 1.461538 / 1.928571 / 1.933333 / 2.538462 / 2.227273 / 2.052632 / 1.2 / 2.5 / 1
Data Analysis
Below is the preformed statistical analysis to find the relation between the three variables. I found the following interpretations by uploading the information to an excel spreadsheet and enabling data analysis. Provided are the null hypothesis and alternate hypothesis that I will be using to test if there is a significant relationship between the three variables.
H0: There is not a significant relationship between the three variables of sex, credit hours and alcohol consumption
HA: There is a significant relationship between the three variables of sex, credit hours and alcohol consumption.
Descriptive Statistics
Q1Sex / Q8CrdHrs / Q16DaysAlcMean / 0.33121 / Mean / 15.07643312 / Mean / 2
Standard Error / 0.037682 / Standard Error / 0.172060697 / Standard Error / 0.11747521
Median / 0 / Median / 15 / Median / 2
Mode / 0 / Mode / 16 / Mode / 2
Standard Deviation / 0.472155 / Standard Deviation / 2.15591435 / Standard Deviation / 1.47196014
Sample Variance / 0.22293 / Sample Variance / 4.647966683 / Sample Variance / 2.16666667
Kurtosis / -1.49474 / Kurtosis / 1.021766367 / Kurtosis / 1.40574165
Skewness / 0.724202 / Skewness / -0.364368623 / Skewness / 0.92836775
Range / 1 / Range / 15 / Range / 7
Minimum / 0 / Minimum / 6 / Minimum / 0
Maximum / 1 / Maximum / 21 / Maximum / 7
Sum / 52 / Sum / 2367 / Sum / 314
Count / 157 / Count / 157 / Count / 157
Above is a summary of the data provided which is a representation of the entire population of 158 students. Included in these measures are mean, median, mode, standard deviation and many more. As you can see from the table most of the students surveyed are males and the most credit hours taken are sixteen. The minimum number of credit hours a student has taken in this semester was 6, equivalent to two classes, and the maximum credit hours as twenty-one. This information helps me by summarizing the many participants so I am able to analyze the data better.
ANOVA
Anova: Single FactorSUMMARY
Groups / Count / Sum / Average / Variance
Q1Sex / 157 / 52 / 0.331210191 / 0.22292994
Q8CrdHrs / 157 / 2367 / 15.07643312 / 4.64796668
Q16DaysAlc / 157 / 314 / 2 / 2.16666667
ANOVA
Source of Variation / SS / df / MS / F / P-value / F crit
Between Groups / 20472.77707 / 2 / 10236.38854 / 4363.60774 / 2.3E-303 / 3.01499
Within Groups / 1097.859873 / 468 / 2.345854429
Total / 21570.63694 / 470
Conducted above is an Analysis of Variance which provides detail differences between the three variables. The average credit hours taken by the 158 students is 15.076. with the number of days consuming alcohol at 2.
Correlation
Q1Sex / Q8CrdHrs / Q16DaysAlcQ1Sex / 1
Q8CrdHrs / 0.044242 / 1
Q16DaysAlc / -0.00922 / 0.098979 / 1
Above is a correlation coefficient which shows a value between -1 and +1 and tells me how strong the variables I am testing are related. I concluded from data analysis that sex and days of alcohol are negatively correlated. Which means those two variables do not have a linear relationship. On the other hand, sex and the number of credit hours are positively correlated.
Regression Analysis
SUMMARY OUTPUTRegression Statistics
Multiple R / 0.046306
R Square / 0.002144
Adjusted R Square / -0.01081
Standard Error / 0.474701
Observations / 157
ANOVA
df / SS / MS / F / Significance F
Regression / 2 / 0.074569739 / 0.037284869 / 0.165459832 / 0.84765437
Residual / 154 / 34.70250032 / 0.225340911
Total / 156 / 34.77707006
Coefficients / Standard Error / t Stat / P-value / Lower 95% / Upper 95% / Lower 95.0% / Upper 95.0%
Intercept / 0.189455 / 0.269672533 / 0.702536777 / 0.483405041 / -0.34328 / 0.72219 / -0.34328 / 0.72219
Q8CrdHrs / 0.009987 / 0.017715935 / 0.563728936 / 0.5737586 / -0.0250106 / 0.044985 / -0.02501 / 0.044985
Q16DaysAlc / -0.00441 / 0.025947739 / -0.169818156 / 0.865376025 / -0.0556658 / 0.046853 / -0.05567 / 0.046853
Conclusion
After finding my results from the tables above I conclude with a .05 level of significance. I accept the null hypothesis. I had a theory that this was true from the beginning. I didn’t think that from the beginning that credit hours had any certain influence on how many days a person consumed alcohol.