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Math 140 Course Project
College of the Canyons

Spring 2022

Student Name: Jason Moss

Due Date: June 2, 2022

Part 1: Categorical Data Analysis

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Part 2: One-Population Proportion Bootstrap Confidence Interval

The lower limit of the confidence interval from the lower box is 0.597, or 59.7%.

The upper limit of the confidence interval from the upper box is 0.663, or 66.3%.

We are 95% confident that the population proportion is between 59.7% and 66.3%.

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Part 3: Quantitative Data Analysis

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IQR = Q3 â€“ Q1 = 8.000 â€“ 3.000 = 5.000

The shape of the data is skewed right.

The more accurate average is the median.

The more accurate spread is the IQR.

Here are the outliers: 72, 63, 59, 50, 49, 48, 45, 40, 36, 35, 33, 30, 28, 25, 24, 21, 20, 18, 17, 16

Part 4: One-Population Mean or Median Bootstrap Confidence Interval

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You must check â€œdata has header row.â€

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Change in project directions: Use only the mean.

The lower limit of the bootstrap confidence interval is 6.729.

The upper limit of the bootstrap confidence interval is 7.910.

We are 95% confident that the population mean average is between 6.729 and 7.910 hours.

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Part 5: ANOVA Randomization Hypothesis Test

Assumptions:

-Yes, we have a census which represents the population.

-Yes, we have 811 > 30.

-Maybe. Independence within a group may not hold since they may know one another.

-Yes. Independence between the two classes since a student in Math 075 is not also in Math 140.

-Yes. Standard deviations are not more than twice as large as the standard deviations for any other

group.

-F = 3.046

Note: There are only two populations present. ANOVA usually is for three or more populations.

However, this should not be a problem.

H0: mu1 = mu2 (categorical variable (campus) is not related to the quantitative variable (amount of

hours of exercise in a week))

HA: at least one population mean is not equal. (categorical variable is related to the quantitative

variable) (CLAIM)

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-F-test statistic = 3.046 < 3.870. The test statistic does not fall in the tail.

-The sample data does not significantly disagree with the null hypothesis.

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-The P-value is 8.5% (or 0.085).

-The P-value is higher than the 5% significance level.

-If the null hypothesis is true, and the P-value is high, then the sample data could have occurred because

of sampling variability.

-Since the P-value is larger than the significance level, we should fail to reject the null hypothesis.

-Conclusion: There is not significant evidence to support the claim that the campus is related to the

amount of hours per week that a student exercises.

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