Statistics Report - Factors Affecting Coffee Consumption In Los Angeles.docx

Your Surname 1 Your Name Subject and Section Professor’s Name March 25, 2019 Statistics Report – Factors Affecting Coffee Consumption in Los Angeles I.

Project Rubric and Copy of the Essay

II.

Introduction Coffee can be considered as an almost indispensable commodity for a lot of people in this

world. It helps us get the ‘kick’ that we need in order to perform the daily tasks that are required of us. In line with this, this study tried to understand the importance of coffee in a very busy city like Los Angeles. This includes the possible relationship between amount of coffee consumption and an individual’s socio-demographic status. To do this, the study utilized a quantitative approach through the use of survey questionnaires. Specifically, data was taken by simply asking random people in the streets to answer survey forms, after asking for the appropriate consent from them. The participants were chosen randomly (random sampling) among all walks of life in order to make sure that the sample population would be representative of the population intended to be studied. III.

Analyzing the Sample 1. Where do you go to get coffee?

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The data taken from the respondents of the survey, suggests that most people in Los Angeles, are buying coffee from corporate brands (i.e., Starbucks, Blue Bottle, etc.) as compared to Local Ones.

2. What is your occupation?

By simply looking at the graph provided above, it can be construed that most people who are drinking coffee are students, followed by self-employed and those having regular jobs, and lastly those who are unemployed. Nevertheless, it is also worth noting that this

Your Surname 3 kind of discrepancy could be due to external factors that could affect the survey (i.e., semestral period vs vacation). 3. Do you commute for work/school?

Most of those who were interviewed commute to work or school. However, this is not directly of a relationship between mode of transportation and coffee consumption.

4. What is your relationship status?

Your Surname 4 A lot of the respondents answered that they are single. On the one hand, this could indicate that single individuals are those who consumes coffee the most. On the other hand, however, it is also worth noting that several extrinsic factors could affect the validity of the data. 5. How many cups of coffee do you drink in a week?

The survey result shows that an average person in Los Angeles, consumes about 7.67 cups of coffee per week. Similarly, this number suggest that most people consumes a cup of coffee per day. And, since the median and the mode are almost similar with each other, it only means that the dataset is more or less distributed.

6. What is your age?

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In the figure above, it could be seen that the average age of people who drinks coffee is 45.3 years old. However, since the median is way lower to the mean, it means that the distribution of such age is unevenly distributed 7. What is your monthly income?

As compared to those provided above, it seems that the relationship between monthly income and coffee consumption is not directly related to each other. Rather, the income of the sample population is not equal and even.

8. How many hours do you sleep on average per night?

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Just like in the previous sections, it seems that the population is even when it comes to the relationship of coffee and hours of sleep. This is exemplified in the even results of the median (n = 6.5) and the mean (n = 6.7). IV.

Statistical Analysis

The scatterplot provided above shows the specific ages of the participants interviewed, relative to their ages. At first glance it seems that the pattern has no trend on its own. Nonetheless, after setting the null hypothesis (“amount of coffee that people drink in a week is INDEPENDENT of the age of people in LA”), and computing for the value of ‘r’, the author

Your Surname 7 found out that the resulting value (n = .204) is not enough to reject the N0. Accordingly, this suggests that the amount of caffeine consumption is independent on the age of the people in Los Angeles.

Just like the one above, the scatterplot herein shows the specific monthly income of the participants interviewed relative to the amount of coffee that they consume. At first glance it seems that the pattern has no trend on its own. Nonetheless, after setting the null hypothesis (“amount of coffee that people drink in a week is INDEPENDENT of the monthly income of people in LA”), and computing for the value of ‘r’, the author found out that the resulting value (n = .27) is not enough to reject the N0. Accordingly, this suggests that the amount of caffeine consumption is independent on the monthly income of the people in Los Angeles.

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The scatter plot herein shows the possible relationship between the amount of coffee that people consume per week as well as the time of sleep per night. The Null hypothesis for this is as follows – amount of coffee that people drink in a week is INDEPENDENT of the average sleep per night of people in LA. After computing for the value of ‘r’, the author found out that the resulting value (n = .217) is not enough to reject the N0. Accordingly, this reaffirms the null hypothesis showing that there is independence between LA people’s average sleep per night and their average coffee consumption. V.

Conclusion All in all, the following graphs have shown that the factors analyzed (e.g., age, monthly

income, and average sleep) are independent of the amount of coffee consumption of LA residents. Nonetheless, it also shows that there are particular trends when it comes to the socio economic and demographic data, when it comes to ‘evenness’ or ‘unevenness’ of the sample

Your Surname 9 population. In the end, even if the results of this study is promising it must be noted that this should not yet be generalized for the whole population without further studies.