StatCrunch logo (home)

Report Properties
Thumbnail:

from Flickr
Owner: mcquadec11
Created: Feb 24, 2019
Share: yes
Views: 129
Tags:
 
Results in this report
 
Data sets in this report
 
Need help?
To copy selected text, right click to Copy or choose the Copy option under your browser's Edit menu. Text copied in this manner can be pasted directly into most documents with formatting maintained.
To copy selected graphs, right click on the graph to Copy. When pasting into a document, make sure to paste the graph content rather than a link to the graph. For example, to paste in MS Word choose Edit > Paste Special, and select the Device Independent Bitmap option.
You can now also Mail results and reports. The email may contain a simple link to the StatCrunch site or the complete output with data and graphics attached. In addition to being a great way to deliver output to someone else, this is also a great way to save your own hard copy. To try it out, simply click on the Mail link.
Group 1 Data
Mail   Print   Twitter   Facebook

Introduction

Group 1 and I designed a survey to examine the exercise and health lifestyles of our friends and colleagues. Our population included American adults. We did not collect a random sample for our survey data. We used convenience sampling to survey our friends via Facebook posts, emails, and text messages. The survey results are also subject to voluntary response as participants were able to choose whether or not they responded to our survey.

 

In our survey, we asked the following questions:

1.     How many days in a week do you do at least 30 minutes of moderate physical activity (an activity that increases heart rate, increases respiration/breathing rate, increases sweating and/or causes muscle fatigue)?

2.     How many hours in a day do you spend sedentary/sitting (ex: eating, commuting, working, watching tv, etc)?

3.     Are you male or female?

4.     How would you rate your overall health: Poor, Good, Very Good, Excellent

 

Looking at a Categorical Variable

The responses to the question "What type of exercise do you do?" are shown in the pie chart below.

Result 1: Pie Chart of Hours per Day Spent Sedentary

Based on the pie chart representing hours per day spent sedentary, one can conclude that a majority of the adults who were surveyed spent approximately 3-10 hours per day sedentary (82.5% of responses). The number of respondents who reported number of hours per day spent sedentary greater than 10 steadily decreased and maxed out at 20 hours per day. It may be possible that due to the wording of question 2, some respondents were unsure if they should include sleeping hours as sedentary. As our group did not plan to include sleeping ours, those respondents who assumed sleeping hours were included as sedentary hours per day would have reported higher number of hours per day sedentary.

 

Next, we will examine a bar plot to determine if hours per day spent sedentary differs among subjects based on how many days per week subjects spend physically active (for at least 30 minutes).  

 

Result 2: Bar plot of Daily Sedentary Hours based on Subjects Number of Weekly Active

 

 

Subjects who reported being physically active five or more days per week were less likely to spend greater than days hours per day sedentary. There was the least variability among subjects who reported being physically active all seven days of the week, who were most likely to report being sedentary for six hours per day, with a range between three and eight hours per day. However, subjects who reported being physically active for one to four days per week reported the greatest variability of daily sedentary hours, ranging from three to twenty hours.

 

 

 

 

 

Looking at a Numerical Variable

 

The responses to the question " How many days in a week do you do at least 30 minutes of moderate physical activity (an activity that increases heart rate, increases respiration/breathing rate, increases sweating and/or causes muscle fatigue)?" are shown in the histogram, boxplot, and summary statistics below.

 

Result 3: Histogram of Days per Week Spent Engaging in Moderate Activity

Result 4: Boxplot of Days per Week Spent Engaging in Moderate Activity

Result 5: Summary stats Days per Week Spent Engaging in Moderate Activity

 

Column

n

Mean

Variance

Std. dev.

Median

Range

Min

Max

Q1

Q3

IQR

Mode

var1

165

4.1575758

4.1091648

2.0271075

4

7

0

7

3

6

3

5

 

Based on the histogram, the shape of the data appears to be slightly skewed to the left, with the tail of the distribution longer on the left hand side than on the right hand side. However, it does not exact fit a left skewed histogram because the mean is typically les than the medium, which is not true in this case because the mean is 4.16 and the median is 4. Also, in left skewed data, the median is typically closer to the third quartile than to the first quartile, which also does not hold true in this data set as the median is 4, which is closer to Q1 (3) than Q3 (6). The center of a skewed data set is best described by the median, however since this data isn’t truly skewed, it is possible to use both the median (4) and the mean (4.16) to describe the center of the data. The data is spread from 0 to 7 days, with respondents covering all seven possible outcomes. However, the IQR (Q3-Q1 or 6-3) is 3. The IQR describes the range of the middle half of the data. This tells us that a majority of respondents are physically active between 3 to 6 days per week. Using the range rule of thumb is reasonable for this data since range/4 (7/4) is 1.75 and the actual standard deviation is 2.03. Therefore, this is a good approximation of the standard deviation as both are approximately 2. Based on the boxplot, there are no outliers in our data, which helps makes the range rule of thumb more accurate as this value is largely affected by outliers. 

 

Looking for a Relationship Between Two Numerical Variables

To determine whether or not there is a relationship between the responses to the questions " How many days in a week do you do at least 30 minutes of moderate physical activity (an activity that increases heart rate, increases respiration/breathing rate, increases sweating and/or causes muscle fatigue)?" and " How many hours in a day do you spend sedentary/sitting (ex: eating, commuting, working, watching tv, etc)?" we look at the scatter plot of the paired data.

 

Result 6: Scatter Plot of Active Days vs. Sedentary Hours Daily

 

 

 

The scatterplot a great deal of scatter.  A few outliers are obvious in the scatter plot: (1 day, 20 hours), (1 day, 22 hours), and (4 days, 20 hours). Outliers in a data set have a significant impact on the correlation coefficient.

 

The correlation coefficient for the paired data is – 0.3076 as shown below.

 

Result 7: Correlation of hours/days of

 

Correlation between var1 and var2 is:
-0.30760913

 

The absolute value of the correlation coefficient, r, is 0.3076. This value is greater than 0.196 from Table A-5 in the textbook. Therefore, we can conclude that there is a statistically significant correlation between the number of active days per week and the number of hours a day spent sedentary. However, by observing the scatterplot, we can conclude that the association between these two variables is not strong.

 

Result 1: Pie Chart of q2   [Info]
Right click to copy

Result 2: Bar Plot With Data graph 2   [Info]
Right click to copy

Result 3: Histogram result 3   [Info]
Right click to copy

Result 4: Boxplot result 4   [Info]
Right click to copy

Result 5: Summary Stats   [Info]

Summary statistics:


ColumnnMeanVarianceStd. dev.MedianRangeMinMaxQ1Q3IQRMode
var11654.15757584.10916482.027107547073635

Result 6: Scatter Plot of 1 on 2   [Info]
Right click to copy

Result 7: Correlation   [Info]
Correlation between var1 and var2 is:
-0.30760913

Data set 1. Group 1 Data Final Set   [Info]
To analyze this data, please sign in.

HTML link:
<A href="https://www.statcrunch.com/5.0/viewreport.php?reportid=84709">Group 1 Data</A>

Comments
Want to comment? Subscribe
Already a member? Sign in.

Always Learning