Mission 1 - Mental Health and Technology

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Fayetteville State University *

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100

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Statistics

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Jan 9, 2024

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STAT E-100 FA 2023 Mission 1: Mental Health in Technology Study: https://www.kaggle.com/datasets/osmi/mental-health-in-tech-survey https://osmihelp.org/research.html Study Context 1) (3 points) In under 250 words, provide three potential motivations (e.g., medical, financial, legal, etc.) behind why this study could have been conducted and who could benefit from the findings. This survey studies how tech employees feel about mental health, if and how their companies manage employee mental health resources, and the possible barriers that workers may have when trying to get help. There are various reasons why this survey might have been administered. One could be to investigate if tech companies are being responsible and involved with their employees’ mental health, another could be in a lawsuit to claim that the company is hostile to employees seeking help. Or simply to gain data about the likelihood tech employees have to suffer from mental illness. Study Design 2) (2 points) Was the study design experimental or observational? How do you know? The study was experimental because the researchers manipulated the independent variable (treatment) and analyzed the effect on the independent variable (yes or no) Data Collection Questions 3) to 5) refer to Mental Health and Technology dataset. 3) (1 points) What type of variable is Country (categorical or quantitative)? What is the level of measurement (nominal, ordinal, interval, or ratio)? In a few sentences, justify your reasoning for the above choices. A country is a categorical and nominal variable because it is non-numerical and there is no particular order to the names of countries. 4) (1 points) What type of variable is Age (categorical or quantitative)? What is the level of measurement (nominal, ordinal, interval, or ratio)? In a few sentences, justify your reasoning for the above choices. Age is a quantitative and ratio variable because it is both numerical and it has an absolute zero. 5) (1 points) What type of variable is Work_Interference (categorical or quantitative)?

STAT E-100 FA 2023 Mission 1: Mental Health in Technology What is the level of measurement (nominal, ordinal, interval, or ratio)? In a few sentences, justify your reasoning for the above choices. Work interference is a categorical variable because it is non-numerical, and ordinal because it has a particular order (never, sometimes, always) Results and Discussion *Please include the R code used to generate the output for the questions below (example on next page) and submit this assignment as a Word document or PDF file. 6) (2 points) Choose one categorical variable and generate a table that shows the count, proportion, or percentage. Write a sentence or two as though you are explaining the findings from the table to a novice audience. Have you sought mental health treatment? No Yes Total 621 633 1254 tally(~treatment, format = "count", data = survey_xlsx_cleaned, margins=TRUE) 7) (2 points) Generate a bar graph using the one categorical variable from question 6). Write a sentence or two as though you are explaining the findings from the visualization to a novice audience. bargraph( ~ treatment, data = survey_xlsx_cleaned, main="Mental Health Treatment", col=c("turquoise"), # horiz=TRUE, xlab="Treatment Status", ylab="Count")

STAT E-100 FA 2023 Mission 1: Mental Health in Technology 8) (2 points) Generate a pie chart using the one categorical variable from question 6). Write a sentence or two as though you are explaining the findings from the visualization to a novice audience. percents <- tally(~treatment, format = "percent", data = survey_xlsx_cleaned) piepercent<- round(percents, 1) pie(percents, radius=1, # Radius of the pie chart labels = piepercent, main = "Sought Mental Health Treatment (%)", # Title of the pie chart col = c("turquoise","yellow"), # Colors of the pie chart cex = 0.75) # Label text size legend("topright", # Positioning of legend c("No","Yes"), # Labels cex = 0.7, # Size of legend fill = c("turquoise","yellow")) # Color of legend 9) (2 points) Generate a contingency table using the one categorical variable from question 6), as well as one other categorical variable. You can condition on a variable if you would like to, or choose not to, but the interpretation should reflect the proper wording. The contingency table can show counts, proportions, or percentages. Write a few sentences about the findings from the table. work_interfere treatment NA Never Often Rarely Sometimes Total No 20.6539075 14.5933014 1.6746411 4.0669856 8.5326954 49.5215311 Yes 0.3189793 2.3923445 9.5693780 9.7288676 28.4688995 50.4784689 Total 20.9728868 16.9856459 11.2440191 13.7958533 37.0015949 100.0000000 tally(~treatment + work_interfere , format = "percent", data = survey_xlsx_cleaned, margins=TRUE) 10) (2 points) Generate a Mosaic plot using the two categorical variables from question 9. Write a sentence or two as though you are explaining the findings from the visualization to a novice audience. 11) (2 points) Generate a bar graph using the two categorical variables from question 9. Write a sentence or two as though you are explaining the findings from the visualization to a novice audience.

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STAT E-100 FA 2023 Mission 1: Mental Health in Technology Example response for the section on variables : “In the dataframe survey_xlsx_cleaned, the variable ‘state’ is a categorical variable. The level of measurement is nominal because there is no ranking or order in the states.” Example response for the section on data visualization : “The pie chart illustrates the percentage of workers who were working remotely or not working remotely. The chart shows that 70.3% of tech workers surveyed did not work remotely, while 29.7% did work remotely.” percents <- tally(~remote_work, format = "percent", data = survey_xlsx_cleaned) piepercent<- round(percents, 1) pie(percents, radius=1, # Radius of the pie chart labels = piepercent, main = "Working Remotely (%)", # Title of the pie chart col = c("turquoise","yellow"), # Colors of the pie chart cex = 0.75) # Label text size legend("topright", # Positioning of legend c("No","Yes"), # Labels cex = 0.7, # Size of legend fill = c("turquoise","yellow")) # Color of legend