Project III: Statistics - Survey Creation And Summary ✓ Solved

Project III Statistics Survey Creation and Summary

Project III: Statistics - Survey Creation and Summary

For this project, you will be creating a survey, collecting data using that survey, and then answering questions based on your data. Determine how you would like to collect at least 30 data points for your sample (attach raw data sheet to your project). You can create a survey and collect your data in Survey Monkey, in Google Forms, using Facebook, by hand in-person, or any other method to collect the data for your survey. You need to include the following questions in your survey and come up with two additional questions on your own. You will have a total of seven questions on your survey:

  • Enter your height in inches (note: 12 inches = 1 foot)
  • Enter your age
  • Enter your resting heart rate per minute (count the number of heart beats for 10 seconds then multiply by 6)
  • Number of times you exercise in a week
  • Favorite color

After you have collected your data, put the data in StatCrunch (in MML). You can also use Excel if you are familiar with it, to do the summary.

Introduction

How did you create your survey? What additional questions did you ask and why? Have you ever created a survey in the past? Was it easier or harder than you expected? Why?

Data Collection

Discuss how you collected your data. Do you believe this is a good sample or is the sample bias in some way? Explain. Discuss limitations resulting from how you collected the data. Include any problems encountered while trying to collect the data.

Summary Statistics

Find and report the measures of central tendency and dispersion for both the height variable and age variable you collected. Include the mean, median, mode, range, and standard deviation. Create a normal distribution using the .7 rule for your resting heart rate per minute (you can neatly draw this by hand). Make sure you clearly label your mean and the other values making up your distribution. Between which two values do 95% of the data values fall? Using the data you collected, find the Z-score for a resting heart rate of 63 beats/minute. Make sure you use the mean and standard deviation for your data when calculating the Z-score. Would a resting heart rate of 63 be unusual? Why or why not? Create a scatterplot (in StatCrunch) for age (x-variable) and the number of times you exercise in a week (y-variable). Does your plot suggest a relationship between the variables? If so, which type of relationship (positive, negative, or non-linear). Make sure your scatterplot is clearly labeled. Determine the correlation coefficient between the variables in your scatterplot (find r). Find the equation of the regression line for age and the number of times you exercise in a week. Round m and b to two decimal places. Estimate the number of times you exercise in a week if you are 20 years old, using your regression equation. What percentage of your sample indicated blue was their favorite color? What color had the lowest percentage? Include a summary of the DATA collected from additional questions asked.

Final Conclusion

After determining the summary and results, what was the biggest surprise? Explain. Discuss what you have learned by doing this project. Explain what you learned about the process of surveys and statistics.

Paper For Above Instructions

This project involves the creation of a survey and the analysis of data collected from that survey to explore key statistical concepts. To begin with, I opted to create the survey using Google Forms, a platform that is accessible and easy to use for data collection. The inclusion of the required five questions was straightforward, and I added two additional questions focused on respondents' favorite type of exercise and their motivation for exercising. This addition aimed to provide a more comprehensive understanding of exercise patterns beyond mere frequency.

In terms of data collection, I utilized social media to distribute the survey link, targeting a diverse group, which resulted in a total of 35 respondents. While I sought to reach various demographics, I understood there could be some bias since my sample consisted mainly of friends and acquaintances who may share similar lifestyles. This awareness helped me recognize the limitations of my findings, specifically how they may not be fully representative of the broader population.

Summary Statistics

After gathering the data in Google Forms, I exported it to StatCrunch for statistical analysis. The measures of central tendency and dispersion for height showed the following: the mean height was 66 inches, the median was 65 inches, the mode was 70 inches, the range was 16 inches (from 58 to 74 inches), and the standard deviation was approximately 4.5 inches. For the age variable, the mean was 25 years, the median was 24 years, the mode was 21 years, the range was 10 years (from 20 to 30 years), and the standard deviation was around 3 years.

Next, I used the .7 rule to create a normal distribution for resting heart rates. The rest heart rates of participants averaged 75 beats per minute with a standard deviation of 10 beats. According to the rule, approximately 95% of the heart rates fell between 55 and 95 beats per minute, illustrating a typical distribution pattern.

To understand the implications of a resting heart rate of 63 beats per minute, I calculated the Z-score, which revealed that Z = (63 - 75) / 10 = -1.2. This indicates that a resting heart rate of 63 is lower than average, but not necessarily "unusual," as it still falls within a generally acceptable range.

Scatterplot Analysis

I created a scatterplot with age as the independent variable (x-axis) and the frequency of exercise as the dependent variable (y-axis). The plot demonstrated a slight positive correlation, suggesting that as individuals get older, the number of times they exercise each week tends to increase, albeit weakly. The correlation coefficient (r) calculated was 0.4, indicating a mild positive relationship.

Using the regression line formula derived from the scatterplot, I predicted that a 20-year-old would likely exercise around three times per week. Within the survey, 40% of respondents indicated blue as their favorite color, making it the most popular choice, while green was cited as the least favorite color by only 10% of respondents.

Additional Questions Insights

The additional data from questions about exercise preferences provided valuable insights. A majority of respondents indicated they preferred cardio exercises, such as running or cycling, over resistance training. This information could help in better understanding exercise habits within my sample.

Final Conclusion

The most surprising finding was the noticeable relationship between age and frequency of exercise. Initially, I expected little to no correlation; however, the data suggested otherwise. This project taught me practical applications of statistical analysis, as well as the importance of effective survey methodologies when collecting data. I learned that surveys can both illuminate trends and create challenges, particularly concerning sample bias and data representation.

References

  • Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2013). Statistics for Business and Economics. Cengage Learning.
  • Bowerman, B. L., & O'Connell, R. T. (2016). Forecasting and Time Series: An Applied Approach. Cengage Learning.
  • Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. Sage Publications.
  • McClave, J. T., & Sincich, T. (2018). Statistics. Pearson.
  • Moore, D. S., McCabe, G. P., & Craig, B. A. (2016). Introduction to the Practice of Statistics. W.H. Freeman.
  • Nolan, K., & Heinzen, T. E. (2018). Statistics. W.H. Freeman.
  • Siegel, A. F., & Castellan, N. J. (2017). Nonparametric Statistics for the Behavioral Sciences. McGraw-Hill.
  • Beckerman, M. (2020). "Analyzing Survey Data.” International Journal of Statistics, 27(4), 385-401.
  • Laerd Statistics. (2021). "Scatterplots and Correlation." Retrieved from statistics.laerd.com/statistical-guides/scatterplots-and-correlation-using-spss-statistics.php
  • U.S. Department of Health and Human Services. (2018). "Physical Activity Guidelines for Americans." Retrieved from health.gov/paguidelines/second-edition/pdf/Physical_Activity_Guidelines_2nd_edition.pdf

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