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Math 10 MPS Lab 11 ANOVA

math 10 mps lab 11 anova & regression for questions 1, use the file ratemp.mpj and the minitab command anovaoneway. make s
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Math 10 MPS Lab 11 ANOVA & Regression
For questions 1, use the file RateMP.mpj and the MINITAB command
ANOVA>ONEWAY. Make sure you choose the Comparisons option and select
the Tukey test.
1.
You want to test the hypothesis: is there a difference in overall
quality due to Division. There are five divisions (some were
combined): Certificate Programs/Other, Creative Arts/Physical Ed,
Social Studies/Humanities/Business,
Language/International/Multicultural, Physical and Health Science
a.
What is response and what is the factor? How many levels?
b.
State the hypotheses in words and parameters.
c.
Run the appropriate one factor ANOVA test. Make sure you select
the Tukey Test under the Comparisons options. Paste the results
here, including a graph comparing the means.
d.
State a detailed conclusion using the both ANOVA results and the
Tukey Test results.
Open the file Calrainfall.MPJ which represents average annual
precipitation (rainfall) in inches and other numeric data about some
California Cities: Latitude in degrees north, Altitude above sea level
in feet, and distance from coast in miles. Use the command
Regression>Fitted Line Plot for Scatterplots, Regression Line, r2 and
Hypothesis test. Use the command Regression>Regression for residuals
and predictions. Unless otherwise specified, conduct all hypothesis
tests with  0.05
2.
You will design a regression Model where Latitude is the
Independent variable and Precipitation is the response. Run
Minitab Stat>Regression>Fitted Line Plot
a.
Make a scatterplot and graph the least square line. Interpret
the slope.
b.
Conduct the appropriate hypothesis test for a significant
correlation between precipitation and latitude.
c.
Find and interpret r2.
d.
Run Minitab Stat>Regression>Regression>Fit Regression Model.
Then find a 95% confidence interval for the expected
precipitation for a city at latitude 40 degrees north using
Stat>Regression>Regression>Predict.
3.
You will design a regression Model where Altitude is the
Independent variable and Precipitation is the response. Run
Minitab Stat>Regression>Fitted Line Plot
a.
Make a scatterplot and graph the least square line. Interpret
the slope.
b.
Conduct the appropriate hypothesis test for a significant
correlation between precipitation and altitude.
c.
Find and interpret r2.
d.
Run Minitab Stat>Regression>Regression>Fit Regression Model.
Click Results and change Fits and Diagnostics to for all
observations.
Then find a 95% prediction interval for the precipitation for a city
at altitude of 150 feet using
Stat>Regression>Regression>Predict.
e.
Analyze the residuals. Which city fits the model best? Which
city fits the model worst?

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