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Answer each question with complete sentences and include all relevant JMP files

ID: 3220685 • Letter: A

Question

Answer each question with complete sentences and include all relevant JMP files requested.

1. What are the two variables of interest? What linear relationship are you interested in exploring?

2. Which data collection technique will be used and why is it best?

3. What sample size is best for this data set and why?

4. Collect the data. Explain any issues you had during data collection. Include the JMP data file with your submission.

5. Is there a statistically significant relationship between the two variables? Describe the relationship in terms of strength and direction. Show your work by including the JMP output file.

6. Develop a linear model of this relationship. Include the JMP output file.

7. Is this a valid model to describe this relationship? Describe the fit of the model. Include the JMP output file.

100

Explanation / Answer

Solution:

variables of einterest is height and weight of 100 students.

sample size=n=100

large sample follows normal distribution according to central limit theorem.

regression equation u obtained is

weight=-110.233+3.514(height)

p<0.05 model is significant

but R2=coefficient of determination =0.2807=28.07% variation in weight is explained by model

rest 100-28.07 %=71.93% remains unexplained

r2 shold me more then only model is good.

here it is less.

there might be some outliers in the data and also influential observations.

Influential observations are points whose removal causes the regression equation to change considerably

Outliers are points that lie outside the overall pattern of the data.

remove them and again plot the regression equation.

check for r2 in the output.

if it is more than model is good.

Answrrs are:

1. What are the two variables of interest?

height and weight

2. Which data collection technique will be used and why is it best?

simple random sampling

sample is random because each people has an equal chance of being chosen.

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