Marketing Research Report

GO HOME GPA, YOU’RE DRUNK!

AN ANALYSIS OF THE CORRELATION BETWEEN DRINKING ALCOHOL AND GPA

1

GO HOME GPA, YOU’RE DRUNK!

AN ANALYSIS OF THE CORRELATION BETWEEN DRINKING ALCOHOL AND GPA

Prepared for Bob Jones, President Kennesaw Vodka Company, Inc.

By Group 2 Lauren Briggs - Associate Joelle Davis - Associate Amethyst Johnson - Associate Lauren McGuinness - Associate Brittany Sorrentino - Associate Alaina Stern - Project Manager

December 2, 2013 2

December 2, 2013 Bob Jones, President Kennesaw Vodka Company, Inc. 15500 Chastain Rd NW Kennesaw, GA 30144

Re: Letter of Authorization Dear Mr. Jones, This letter of authorization is to formally document the authorization that has been granted to Group 2 for the purposes of performing a marketing research project studying the correlation of college GPA to drinking and types of alcohol being consumed for Kennesaw State University students. Group 2 will be performing this analysis. The group associates are Lauren Briggs, Joelle Davis, Amethyst Johnson, Lauren McGuinness, and Brittany Sorrentino. The project manager is Alaina Stern.

The conditions of this authorization include the following: soliciting KSU students for survey information via on-site paper surveys, compiling and analyzing the data, formal report prepared

by December 2, 2013, and presenting our findings and recommendations in-person on December 3, 2013. The cost for this study is $2,000 as it is a student-only project, and there are no additional special conditions. Group 2 looks forward to presenting its findings to you tomorrow.

Sincerely, Lauren Briggs Joelle Davis Amethyst Johnson Lauren McGuinness Brittany Sorrentino Alaina Stern

3

December 2, 2013 Bob Jones, President Kennesaw Vodka Company, Inc. 15500 Chastain Rd NW Kennesaw, GA 30144

Re: Letter of Transmittal Dear Mr. Jones, I hope this letter finds you well. I am pleased to inform you that Group 2 has completed its analysis and is ready to present its findings tomorrow morning to you. As a reminder, the purpose of this marketing research project is to study the correlation of college GPA to drinking and types of alcohol being consumed for Kennesaw State University students. The study will be used to design a marketing campaign for a new brand of vodka being rolled-out by your company in 2014. The group associates are Lauren Briggs, Joelle Davis, Amethyst Johnson, Lauren McGuinness, and Brittany Sorrentino. The project manager is Alaina Stern, and she is your primary contact for any additional questions, comments or concerns. Alaina is best reached via email at astern2@students.kennesaw.edu.

In general, Group 2 found a negative correlation between GPA and Wine. Therefore the alcohol segments we would recommend is beer and liquor. For further research, we suggest that you review the KSU Fact Book and our survey results. Personally, the group had pre-conceived notions of what to expect from the survey, but the results surprised all of us. We greatly appreciate this opportunity and look forward to speaking tomorrow.

Sincerely, Lauren Briggs Joelle Davis Amethyst Johnson Lauren McGuinness Brittany Sorrentino Alaina Stern

4

TABLE OF CONTENTS

SECTION TITLE

PAGE

EXECUTIVE SUMMARY

X

INTRODUCTION

7

RESEARCH OBJECTIVES

8

METHODOLOGY

9

RESULTS

9-13

LIMITATIONS OF THE STUDY

14

CONCLUSIONS AND RECOMMENDATIONS

15

Appendices

Appendix A

16-20

Appendix B

21-22

Appendix C

23-24

5

EXECUTIVE SUMMARY Most people feel that students have trouble balancing alcohol consumption and school.

Instead of a negative correlation between school and drinking, what if statistics could show a positive correlation between alcohol consumption and GPA. The purpose of the marketing research project is to determine if a positive relationship exists between a high rate of alcohol consumption and a high semester GPA for students at Kennesaw State University. What happens when you only consume three drinks per week, as a student does your chances of getting a higher grade point average vary or are there outside variables that affect such actions?

Our overall objective is “to determine if a positive relationship exists between a high rate of alcohol consumption and a high semester GPA for students at Kennesaw State University�. We have developed an interest in discovering whether or not a high rate of drinking truly affects the grade point average of college students. We are interested in learning about the ways, if any, that students balance out the heavy loads of school work and their own active social lives.

For our primary data we will be distributing a survey in classrooms, on our various social media pages and via a QR code that will link to the survey. We will be asking mostly close ended questions involving student’s grades, potential test anxiety, and how they feel alcohol affects their performance in school. The secondary data that we will be using will be the KSU Fact Book and a survey that was conducted over the summer on Kennesaw State University students that has a section on student drinking and a section on student grades.

Based on the research procedures and measures taken to perform marketing research, we have discovered both positive and negative correlations and significant relationships between the dependent variable (GPA) and our independent variables (types & frequency of alcohol consumption). This report goes into detail on our findings and both graphically and statistically represent the target population.

6

INTRODUCTION We hear the horror stories every day with young adults passing due to fatal car accidents, severe injuries, suicidal attempts, assault, and even sexual abuse due to the overuse of alcohol consumption. Statistics steadily show that not only are the students affected by these drastic changes, but also college communities and families of these students. I am reminded of a famous quote that is constantly stated around college campuses, “Know your limit.” This quote always prompted me, as a young adult, excessive drinking is not necessary because things can easily spiral downhill when you don’t have full control over your bodily functions. Excessive drinking is where many college students go wrong; perhaps they don’t know their limit. As a result, most people feel that students have trouble balancing alcohol consumption and school. Instead of a negative correlation between school and drinking, what if statistics could show a positive correlation between alcohol consumption and GPA. Our study will be conducted using the students of Kennesaw State University, our focus will lie solely on the correlation on the campus. The purpose of the marketing research project is to determine if a positive or negative relationship exists between a high rate of alcohol consumption and a high semester GPA for students at Kennesaw State University. According to a study Kennesaw State University actively participated in, conducted in 2000 by the Educational Development Center of Newton‚ Massachusetts‚ “75 percent of KSU students have three or fewer drinks in a week's time. Sixty three percent have only one or zero drinks during a week's time. Seventy− six percent of KSU students consume four or fewer drinks when they party‚ and 73 percent of KSU students have three or fewer drinks when on a date. Eighty−three percent of KSU students describe themselves as either abstainers or light drinkers.” The media has focused the attention on college students who excessively consume alcohol in short periods of time. As mentioned earlier, not every student is a social drinker and certainly not every student drinks to get drunk.

We all understand and have heard many times the negative effects that excessive alcohol consumption can have on our bodies, brains, and day to day lives. What happens when you only consume three drinks per week, as a student does your chances of getting a higher grade point average vary or are there outside variables that affect such actions?

7

RESEARCH OBJECTIVES Our overall objective was “to determine if a positive relationship exists between a high rate of alcohol consumption and a high semester GPA for students at Kennesaw State University”. It is a widely-spread assumption that while in college, students who consume a large amount of alcohol at a frequent rate (2 or more drinks consumed more than 2 times a week) will consequently suffer a lower GPA for the semester. In actuality, many students face GPA requirements through student organizations, scholarships, and grants. However, these individuals are still able to make time for leisure. Dozens of social events with heavy drinking take part within Greek life and other student organizations, meaning that even though students may be required to maintain a 3.0 GPA, they may drink to a level of intoxication on a regular basis. Our purpose was to uncover to what extent this is true. In an effort to break down the aforementioned objective into more specific segments, we conducted a variety of analyzations. Objectives included: ● to determine how often students have consumed beer, wine, and liquor within the past six months ● to determine whether or not a relationship exists between a high rate of beer consumption and GPA ● to determine whether or not a relationship exists between a high rate of wine consumption and GPA ● to determine whether or not a relationship exists between a high rate of liquor consumption and GPA We have developed an interest in discovering whether or not a high rate of drinking truly affects the grade point average of college students and will be conducting this study throughout the course of the semester. Our goal is not to discover a means for students to feel as though a high rate of drinking is harmless to their academic life. Instead, we are interested in learning about the ways, if any, that students balance out the heavy loads of school work and their own active social lives. Any methods obtained through this research can be used to aid students who place emphasis on maintaining both strong academic and recreational lifestyles METHODOLOGY For our primary data we distributed surveys throughout both on and off campus locations. We administered the survey exclusively to Kennesaw State University undergraduate students as we felt that this demographic segment had the highest relation to our objectives.

Sampling Plan Each member of our group collected approximately 27 surveys from various undergraduate students. Ultimately, we collected 165 surveys before beginning our data input. We chose self8

administering as we felt that this was the most convenient way for students to fill out the survey and the fastest way to collect the data. By having collected this number of surveys, our results would be accurate to approximately + or – 8.5%.

Data gathering instrument Our survey consisted of 16 questions targeting both the drinking habits and academic characteristics of participants. Specifically, questions asked for age, gender, major, GPA, types of alcohol consumed (if any), frequency of consumption, hours spent studying, and more.

Data Collection The data collection process spanned over two weeks in early November. During this time, all members accumulated approximately 28 completed surveys. We worked on the honor system in our group so that no supervision would be administered during the gathering process. Because we extended surveys on no particular schedule and on our own times, we periodically checked data to see how the data collection was going in case someone needs help collecting surveys. As a group we were able to collect these surveys by going to different classes of professors that we know and asking that their students fill out the questionnaire.

RESULTS

Collectively as a group we gathered data from a sample size of 165 students who currently attend Kennesaw State University. Using the software SPSS, the raw responses were coded, the respondent’s answers were transformed into data. With this data, a number of different statistical amylases can be preformed. By running certain tests and functions, statistical analyses transform the raw data into meaningful, beneficial, and useful information. The tests and amylases vary from simple frequency tables, to one way ANOVAs, and bivariate correlation calculations.

By administering the surveys in print and by hand, the control of selecting respondents increases.

In order to ensure an accurate reflection of the target population it is important to have an evenly distributed and well representative sample. By running simple frequency tables, some key insights about the demographics and key aspects of the selected sample. Below is a frequency bar graphs, pie charts, and other figures that reveals the identities of our questionnaire respondents.

9

AGE OF RESPONDENTS 49 38 34 31 29 27 25 23 21 19 17 0

5

10

15

20

25

30

35

40

**The majority of people surveyed fell between the ages of 18-22 years old; with 18 years being the most frequent and tallying in at 36 of our sample representing 21.8%. It is important to take into consideration missing values; that being said age could be considered somewhat of a sensitive subject, six participants in the survey failed to answer or skipped this question.

CLASS STANDING

Freshman Sophomore Junior Senior

**Just about half of the survey participants are seniors, while sophomores represent less than 10% of peopled surveyed. The fact that seniors make up 46% of respondents can be partly

10

contributed by a sampling error caused because everyone on our team are seniors. Both academic standings of junior and the freshmen are approximately one-fourth of the total sample.

GENDER

Male Female

**The gender ratio of our selected sample is almost exactly evenly distributed. With slightly more male respondents, there is a 52% and 48% split.

The very first question on the questionnaire asked the respondent to answer yes or no, indicating whether or not they have consumed an alcoholic beverage in the past six months. The frequency distribution Table A concludes that 126 surveyed individuals have had a drink; while 23% answered they have not had a drink in the past six months.

Because alcohol has various forms and potencies it was important to distinguish what type and amount of alcohol was being considered. Table B & Figure B summarize the types of drinks consumed. The top answer given, making up 36% of total responses given was ‘all of the above’.

The categories and types of alcohol choices were beer, wine, liquor and a combination. The second most popular category chosen by participants was both beer and liquor. The option with the least amount tallies was wine. Figure C respectively shows each type of alcohol and the number of times per week through a bar graph. The number one combination amongst the students surveyed was liquor and they consumed it 1-3 times a month regularly. However, surprisingly the second most popular answer was wine consumed once a month.

The last question on our survey asked the respondent to indicate the cumulative GPA. Figure D & Table D located in the appendix shows frequency and range of GPA’s given by participants.

The highest GPA was a 4.0 with three answers and the lowest was 2.15 which was only given once. The average Grade Point Average of the whole sample is calculated out to equal 3.32.

While frequency distributions and descriptive statistics are very useful in identifying major trends and measuring central tendency; statistical analyses such as one-way ANOVA’s and 11

bivariate correlation tests are crucial to our marketing objectives. The importance of knowing which variables affect the dependent variable (GPA) and understanding how strong, if any, relationship exists.

Our research objective was to find out if a relationship between drinking alcohol and Grade Point Average existed. To compare the two variables in a broad fashion, to simply see if a relationship exists between GPA and alcohol consumption, we ran a one-way ANOVA (Table E). The significance level of this reported at .03, which means that a relationship does exist between GPA and alcohol consumption within the past six months. To see how strong of a relationship exists, Table F, shows the results of a bivariate correlation analyses. The Pearson Correlation indicates how strong and what type of relationship exists. The correlation value is .181, meaning a weak relationship exists because it is close to zero. However, do note that the value is positive; meaning as one variable increases so does the other.

When analyzing the data it is important to take in multiple independent variables into account when trying to find a relationship to the dependent. The graph below calculated the general frequency of the number of hours spent studying as stated by questionnaire participants.

HOURS SPENT STUDYING 80 70 60 50 40 30 20 10 0

Less than 1 hour

1-4 hours

5-9 hours

10-14 hours

More than 15 hours

** This chart displays the hours per week surveyed students claimed when asked.

Separate tests were run on each type of drink, Tables G, H, & I, all show both the significance level from a two-tailed test and the p-value of the Pearson Correlation. All three bivariate analyses showed no relationships between the type of alcohol consumed and the number of hours spent studying.

12

In efforts to further investigate our research objectives it was important to take it one step further and breakdown the types of alcohol and further explain the nature of the relationship between the two variables, age and consumption frequency. Because age is a continuous ratio type of variable and the independent variable is a categorical ratio, Figure J & Table J, show the frequency tabulations and significance level of both variables. There are two major indications and findings based on these analyses. The first significant factor is from running frequency of wine against age. We are able to conclude and state; we will reject the null hypothesis. This is because the two-tailed sig. value is .02; which is less than .05. The second factor worth mentioning is the negative existence of a relationship between frequency of liquor consumption and age. This is shown through the negative p-value of -.042.

Our main research objective was broad and aimed to determine if and to what extent a relationship exists between alcohol consumption and cumulative grade point average. The last analyses discussed, Tables K, L, & M, are some if not the most important statistical analyses preformed from our data. The first table of the three bivariate tests between alcohol consumption and GPA uses beer as its variable. The p-value us -.178, meaning a negative correlation between the two variables exist. However the two-tailed sig. value is .06 which is greater than .05; so we accept the null hypothesis. The second correlation analysis shows the p-value of -.223 and a sig. value of .018. From these factors we should advise to reject the null hypothesis and accept that there is a negative correlation and a significant statistical relationship between liquor consumption and GPA. LIMITATIONS As with any conducted research, a number of limitations exist that may skew our survey results and conclusions. These can lead to an acute number of inaccuracies in our study, so we have to make sure that we exhaust all measures while both preparing and conducting for the survey.

First of all, we will likely only survey approximately 150 people given that the 6 of us will each survey 25 people each. Seeing how this year we have over 24,600 students, this means we will only be surveying 1 out of every 984 people. After all, due to restrictions on time it may be our only choice to survey approximately 25 students per group member.

Our second limitation lies in the inability to accurately gather the same amount of responses from the university’s non-traditional and online students. Prior to Daniel Papp becoming the university’s president in 2006, the school was predominantly made up of non-traditional students. Successful efforts have since been made to increase the amount of traditional students in attendance and the campus has been changing dramatically. Right now, traditional students make up the majority of the students at KSU. This means that the surveys will be skewed towards traditional a student which already forms an imbalance in the sample.

13

Thirdly, another limitation that we may not be able to control in the surveys are independent factors such as forces outside of drinking. Many students in college juggle two to three jobs throughout the week, stress with bills, family, on top of their school work. These factors can ultimately limit our surveys honest responses in how great their grade point averages are and can also play a role in the deterioration of their GPA. I also believe the lack of time students have to sit, take surveys, and properly fill them out will be another limitation that will cause our result to produce outliers. Again, students are always on the go, and grabbing their attention is a tedious task to conduct. As Group 2, we will face the challenge and overcome it.

Other limitations or restrictions on resources may arise during the course of our research.

Though we cannot avoid them, the team can prepare for these occurrences. As of now, we have built a strong foundation and a survey constructed to produce relevant and valuable content from respondents. Conducting survey research has shown to have limitations, but Group 2 will look to challenge and face the limitations by cross sectional sampling, “improved response techniques”, and considering outside independent factors for our respondents. Our goal is to provide public information that serves as the most relevant data concerning college student’s grade point average and drinking habits.

CONCLUSION & RECOMMENDATIONS Our main research objective was to determine if any type of relationship exist between alcohol and GPA . In conclusion, through data gathering, preparation, validation, entry, and statistical analyses we conclude that a relationship exists between GPA and Alcohol consumption within the past six months. The Pearson Correlation signifies that the relationship between GPA and alcohol consumption is positively correlated. We also achieved one of the other research objectives and have determined that the only type of alcohol that has a statically significant relationship with GPA and consumption of wine. This relationship is has a negative correlation as indicated by a -.223 value for the Pearson Correlation.

Our recommendations, formed from our marketing research procedures are based on our selected sample which is representative of the entire KSU student body. The bar graph titled ‘type and frequency of alcohol’ (Figure C) and going off the basis of the existence of a relationship; we recommend choosing beer for promotional efforts. This is our recommendation because both liquor and wine consumption have a negative correlation with GPA. As a secondary recommendation for other promotional tactics such as options and packaging, the second most appealing type of alcoholic beverage preferred by the sample was liquor. Even thought the pvalue shows a negative between liquor and GPA; a value of -.179 is not very significant because it is very close to zero. Beer and liquor are the most popular and most frequently consumed.

14

APPENDICIES APPENDIX A Table A Consumed Alcohol in 6 Months?

Cumulative Frequency Valid

Valid Percent

Percent

Yes

126

76.4

76.8

76.8

No

38

23.0

23.2

100.0

164

99.4

100.0

1

.6

165

100.0

Total Missing

Percent

System

Total

Table B Drink Types Consumed Cumulative Frequency Valid

Valid Percent

Percent

Beer

4

2.4

3.2

3.2

Wine

2

1.2

1.6

4.8

Liquor

9

5.5

7.2

12.0

60

36.4

48.0

60.0

Beer and Wine

7

4.2

5.6

65.6

Beer and Liquor

27

16.4

21.6

87.2

Wine and Liquor

16

9.7

12.8

100.0

125

75.8

100.0

40

24.2

165

100.0

All of above

Total Missing

Percent

System

Total

Table D Descriptive Statistics N

Minimum

Grade Point Average

145

Valid N (listwise)

145

2.15

Maximum 4.00

Mean 3.3191

Std. Deviation .38110

15

Table E ANOVA Grade Point Average Sum of Squares

df

Mean Square

F

Sig.

Between Groups

.684

1

.684

4.832

.030

Within Groups

20.231

143

.141

Total

20.914

144

Table F Correlations Consumed

Grade Point Average

Grade Point

Alchol in 6

Average

Months?

Pearson Correlation

1

.181

Sig. (2-tailed)

*

.030

N

145

145

*

1

Consumed Alchol in 6

Pearson Correlation

.181

Months?

Sig. (2-tailed)

.030

N

145

164

# of hrs spent

Frequency of

studying

beer

*. Correlation is significant at the 0.05 level (2-tailed).

Table G Correlations

# of hrs spent studying

Pearson Correlation

1

Sig. (2-tailed)

Frequency of beer

.044 .631

N

163

124

Pearson Correlation

.044

1

Sig. (2-tailed)

.631

N

124

125

16

Table H Correlations

# of hrs spent studying

# of hrs spent

Frequency of

studying

wine

Pearson Correlation

1

.030

Sig. (2-tailed)

Frequency of wine

.740

N

163

124

Pearson Correlation

.030

1

Sig. (2-tailed)

.740

N

124

125

Table I Correlations

# of hrs spent studying

Pearson Correlation

# of hrs spent

Frequency of

studying

liquor 1

Sig. (2-tailed) N Frequency of liquor

Pearson Correlation

-.035 .696

163

125

-.035

1

Sig. (2-tailed)

.696

N

125

126

17

Table J Correlations

Frequency of beer

Frequency of

Frequency of

Frequency of

beer

wine

liquor

Pearson Correlation

1

N Frequency of wine

Frequency of liquor

Age

125

Pearson Correlation

.151

Sig. (2-tailed)

.094

N

125 **

Pearson Correlation

.416

**

.018

.094

.000

.848

125

125

122

1

*

.151

Sig. (2-tailed)

Age

.416

.227

.211

*

.011

.020

125

125

122

*

1

-.042

.227

Sig. (2-tailed)

.000

.011

.641

N

125

125

126

123

Pearson Correlation

.018

.211

*

-.042

1

Sig. (2-tailed)

.848

.020

.641

N

122

122

123

159

**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Table K Correlations

Frequency of beer

Pearson Correlation

Frequency of

Grade Point

beer

Average 1

Sig. (2-tailed) N Grade Point Average

Pearson Correlation

-.178 .060

125

112

-.178

1

Sig. (2-tailed)

.060

N

112

145

18

Table L Correlations

Grade Point Average

Grade Point

Frequency of

Average

wine

Pearson Correlation

1

-.223

Sig. (2-tailed)

.018

N Frequency of wine

*

Pearson Correlation

145

112

*

1

-.223

Sig. (2-tailed)

.018

N

112

125

*. Correlation is significant at the 0.05 level (2-tailed).

Table M

Correlations

Grade Point Average

Pearson Correlation

Grade Point

Frequency of

Average

liquor 1

Sig. (2-tailed) N Frequency of liquor

Pearson Correlation

-.179 .058

145

113

-.179

1

Sig. (2-tailed)

.058

N

113

126

19

APPENDIX B Figure B

DRINK TYPES CONSUMED Beer Wine Liquor

All of above Beer and Wine Beer and Liquor Wine and Liquor

Figure C

20

Figure D

Figure J

AGE VS TYPE & FREQ 30.00 25.00 20.00

15.00

Beer Wine

10.00

Liquor

5.00 0.00 Never

Less than 1-3 drinks 1 drink 2-3 drinks 4-5 drinks Daily 1 drink a a month per week per week per week drinking month

21

APPENDIX C PRESENTATION SLIDES

22

23