Stats project

Statistics Project

For my statistics project, I chose to look at alcohol consumption and decision making, as well as

the effect that Netflix viewing (amount of viewing per week) has on productivity levels. Each of these

topics are of interest to me, as well as relevant to my age demographic and sample size, so I was eager to

see the results.

I chose to look at the relationship between alcohol consumption and poor decision making

because let’s be honest, everybody’s judgement seems to be a little skewed when intoxicated. Quite

frankly, I have seen far too many of my friends make questionable decisions when consuming large

amounts of alcohol, therefor it led me to the hypothesis (H1) that people are more likely to make poor

decisions based off the amount of alcohol they consume.

I chose to look at the effect that Netflix viewing (per hour) weekly has on productivity levels,

because I often blame Netflix for me struggling to keep up with classwork and work at my job. Quite

frequently I will say, “I have to wait until the semester is over to start XXX series on Netflix” due to the

effect that it has on my own personal productivity level. With the rise in popularity of sites like Netflix,

Hulu, HBO Go, etc., and the act of “binge watching” becoming so popular, I felt this was an extremely

time-relevant study to run. I was interested to see if my own assumption was consistent with others in my

age demographic/sample. My own experiences led me to the hypothesis (H2) that there would be a

significant relationship between the amount of Netflix watched (per hour) in a week and the decreased

levels of productivity.

Sample Group/Size

For both studies, I chose to conduct a short survey that was distributed to the same sample group

(six individuals: four females and two males). I chose to keep the same sample for both studies because I

felt that the group was relevant to both hypothesis’ being tested, as all people included in the sample were

of the typical age demographic to consume large amounts of alcohol more frequently (at bars, clubs,

parties, etc.) and more likely to act in a reckless manor, as well as the typical age demographic to binge

watch Netflix and have that influence their productivity level. All subjects were between the ages of 22-

28 (one 28-year-old, two 25-year-olds, one 23-year-old, and two 22-year-olds) and currently either

enrolled in school and/or held a steady job. The questions for the surveys were as follows:

Survey Questions

For the first study (H1), the subjects were asked to report the amount of drinks they consume per

week (1-3, 4-7, 8-11, 12+ or none) and whether they believed those consumption rates influenced their

decision making (specifically whether they believed it caused them to make poor decisions), by

answering “Yes” or “No.” For the second study (H2), the subjects were asked to report how many hours

of Netflix they watched per week (1-3, 4-7, 8-11, 12+ or none) and the likelihood of that person choosing

to watch Netflix over doing their homework/work that week (productivity levels) by filling out a Likert

scale, ranging from 1 (very unlikely) to 5 (very likely), with 3 being neutral.

Tests

For the first study (H1) looking at alcohol consumption and decision making, I chose to run an

Independent T-test. This was the appropriate test to run because it looks at two independent groups on the

same dependent variable and determines whether there is evidence that the means are significantly

different. For the second study (H2) looking at amount of Netflix viewed per week and its effect on

productivity levels, I chose to run a Spearman’s Rho. This was the appropriate test to run for this type of

study because it looks at ordinal-level data and measures the strength of association between 2 variables,

where r=1 means a strong positive correlation and r=-1 means a strong negative correlation.

Results

For H1, an Independent T-test was conducted to compare the amount of alcohol consumed and

the effect it has on your decision making (more specifically, the more alcohol consumed, the worse

decisions you make). There was not a significant difference between amounts of alcohol consumed and

poor decision making because all respondents reported that they make poor decisions when consuming

alcohol, regardless of the amount consumed.

For H2, a Spearman’s Rho was conducted to examine the relationship between the amount of

Netflix (hours) watched per week and the likelihood of choosing to watch Netflix over doing homework

and/or work (productivity levels). A strong nonsignificant relationship was found between the amount of

Netflix (hours) watched per week and levels of productivity, however r (6)= .636, p=.175.

Descriptive Statistics

The sample for both studies was made up of participants that were all Caucasian (100%), female

(67%) and had an average age of 24.17.

For H1 (the relationship between alcohol consumption and poor decision making), 16.7% of the

sample group answered that they consumed approximately 1-3 drinks per week, 16.7% said they

consumed approximately 4-7 drinks per week, 16.7% said they consumed approximately 8-11 drinks per

week, 33.3% consume 12 or more drinks per week, and 16.7% consume 0 drinks per week. Running the

frequencies and central tendencies showed that the average answer (mean), when asked how many drinks

were consumed per week, was 3.17 (averaging a little more than 8-11 drinks per week), the median was

2.5, and the mode, or most often answered, was 4 (consuming 12+ drinks per week). There was a standard

deviation of 1.47 found when running the frequencies for amount of alcohol consumed per week.

Regarding the likelihood to make poor decisions when consuming alcohol, the mean, median, and mode

were all 1 (meaning that all participants answered “yes” when asked if they felt they were more likely to

make poor decisions after consuming larger amounts of alcohol).

For H2 (the effect that Netflix viewing has on productivity levels), 16.7% of the sample group

answered that they view approximately 1-3 hours of Netflix weekly, 50% answered that they view

approximately 4-7 hours of Netflix weekly, and 33.3% answered that they view 8-11 hours of Netflix

weekly. Regarding the likelihood of choosing Netflix over work, 16.7% of the sample group answered

that they were very unlikely to choose watching Netflix over completing a work and/or school tasks,

16.7% answered that they were neutral, 33.3% answered that they were pretty likely to choose watching

Netflix over completing work and/or school tasks, and 33.3% answered that they were very likely to

choose watching Netflix over completing work and/or school tasks. Running the frequencies and central

tendencies showed that the average answer (mean), when asked approximately how many hours of

Netflix the subject watched a week, was 2.17 (averaging a little more than 4-7 hours per week), the

median was 2, and the mode, or most often answered, was 2 (watching 4-7 hours of Netflix per week).

There was a standard deviation of .75 found when running the frequencies for amount of Netflix (hours)

watched per week. Regarding the likelihood to choose watching Netflix over completing work and/or

school work, the average answer (mean) was 3.67, meaning that on average the sample group was fairly

neutral (but a bit more skewed towards pretty likely) to choose watching Netflix over completing work,

the median was 4, and the mode, or most often answered, was 4 (pretty likely to choose watching Netflix

over completing work). There was a standard deviation of 1.51 found when running the frequencies for

the likelihood to choose watching Netflix over completing work.

Conclusion

In conclusion, there was no significant difference found between the amounts of alcohol

consumed and poor decision making. There was no significant difference found because all six

respondents answered that they make poor decisions when drinking alcohol, regardless of the amount

consumed (maybe my friends just make poor decisions in general?). One way in which this study could

have been conducted better would be to push out the sample size and get answers from differing age

demographics and look at it that way. This would be beneficial because it would make the study more

thorough, but it would also take into factor maturity level (which I believe plays a significant role in the

amount of alcohol you may consume and the decisions you make). It is important to note that all subjects

in the study were 22-28 years of age, were not married, and had no children. This could also affect the

way in which they make decisions, as compared to somebody who is married and/or has a child.

As for amount of Netflix viewing and its effects on productivity levels, there was a strong

relationship between the two, however the relationship was not significant. There was a negative

correlation, meaning that the more Netflix viewed per week, the less productive one is likely to be,

however that relationship was not significant enough to support the hypothesis. I believe that this study

would also benefit from broadening the sample size and taking into consideration other age groups, as

well as maybe separating out the effects it has on students work and the effect it has on an employee’s

job. If you were to separate these two elements out, you may receive different results, seeing as there

would be a lot more at stake when it comes to an employee’s job versus a student’s homework. It is

important to note that of the six respondents in the study, 3 currently had fulltime jobs and 3 were

currently enrolled at a university working towards a Bachelor’s degree.

All in all, the hypothesis of both studies were supported to some degree. Although nonsignificant,

H2 was supported in the results. However, for H1, I had originally assumed that the more alcohol you

consume, the more likely you are to make poor decisions, but as it turns out, regardless of amount, when

alcohol is involved, one seems to be more likely to self-report making bad decisions.

Tables/Charts

Independent T-Test (H1):

Frequencies (H1):

Central tendencies (H1):

Spearman’s Rho (H2):

Frequencies (H2):

Central tendencies (H2):