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Owner: nursecandy
Created: Mar 20, 2019
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FOOTBALL SURVEY 2

I.             Introduction

A.
Our group designed a survey to learn many hours how our friends, family, coworkers, and acquaintances watch television with a focus on football and their opinion the outcome of the Super bowl.  We polled this population using email, Facebook, and through interview. We did not obtain a random sample for this survey.  We have a convenience sample with a voluntary response aspect, as not everyone we asked took the time to respond. The total response for our survey was one hundred and fifty two.

B.

1.       In a typical week, how many hours of TV do you watch?

2.      In a typical week, how many hours of sports do you watch?

3.      Do you watch football?

4.      Who do you think will win the Super Bowl?

New England Patriots, LA Rams, I don’t know

II.           Looking at a Categorical Variable

A.
The responses to the question "Do you watch football?" are shown in the pie chart.

Result 1: Pie Chart Responses to Watching Football?

Result 1: Pie Chart With Data   [Info]

From the pie chart above we were able to ascertain that 54 out of 152 respondents or 35.5% did not watch football.  While 98 or 64.5% did watch football.

Result 2: One sample Proportion with summary

95% confidence interval results:
p: proportion of successes for population
Method: Standard-Wald

Result 2: One sample proportion confidence interval   [Info]

### One sample proportion confidence interval:

Outcomes in : Do You Watch Football
Success : Y
p : Proportion of successes
Method: Standard-Wald

95% confidence interval results:
VariableCountTotalSample Prop.Std. Err.L. LimitU. Limit
Do You Watch Football981520.644736840.0388190170.568652970.72082072

Interpretation of the confidence interval: Above is the 95% confidence interval results for the portion of this group that answered yes to the question “Do you watch football?” A 95% confidence interval means that if we were to select many different samples of size n=152, approximately 95% of these samples would result in confidence intervals that contain the true proportion p. Thus we interpret the above results by saying we are 95% confident that our confidence interval contains the true proportion, i.e., we are 95% confident the true proportion of our population that would answer yes to this question is between 0.569 to 0.721.

The margin of error is E= (0.721-0.645)/2=0.076/2 = 0.038 (margin of error).

III.        Looking at a Numerical Variable

A.

The responses to the question "In a typical week, how many hours of sports do you watch?" are shown in the histogram and the summary statistics below.

Result 3: Histogram

Result 3: Histogram of "Hours of Sports Watched per Week"   [Info]

Result 4: Summary Statistics for Total Hours of Sports Watched

Result 4: Summary Stats "Hours of Sports Watched per Week"   [Info]

### Summary statistics:

ColumnnMeanVarianceStd. dev.MedianRangeMinMaxQ1Q3
Hours of Sports Watched1523.026315814.5555943.815179522002005

B.

A 95% confidence interval for the population mean is shown below.

Result 5: One sample T statistics with data

Result 5: One sample T confidence interval   [Info]

### One sample T confidence interval:

μ : Mean of variable

95% confidence interval results:
VariableSample MeanStd. Err.DFL. LimitU. Limit
Hours of Sports Watched3.02631580.309451921512.4149013.6377306

Interpretation of the confidence interval: A 95% confidence interval means that if we were to select many different samples of size n=152, approximately 95% of these samples would result in confidence intervals that contain the true proportion mean µ. Thus we interpret the above results by saying we are 95% confident that our confidence interval contains the true population mean.  In other words, we are 95% confident that within our population, the average person watches sports between 2.4 and 3.6 hours a week.

The t-distribution was used because the population standard deviation is unknown.