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Please download this Word document, and answer the questions / include output /
etc. under each question.
Note:
â?¢ This is an individual project, and not a group project. Your work should be your
own, original work.
â?¢ All numerical and graphical results are to be produced in JMP
â?¢ Be sure to include all relevant work / output for full / partial credit, including
graphs, charts, and other information for each problem
â?¢ All submissions must be electronic â?? typed â?? no handwritten work!
o Type responses and paste JMP outputs directly into this document.
â?¢ This assignment should be submitted to the D2L dropbox, in PDF format. It is due
Friday, May 11, 2018 by 11:59pm. No late submissions will be accepted.
———————————————————————————————————–Data Set Preparation
1. Using the â??Toyota Corollaâ? data set on D2L (Content â?? â??JMPâ? â?? â??JMP Data Setsâ?
folder), we will be interested in analyzing the â??Priceâ? of a car as the dependent variable
(Y). Please select one independent variable (X) you think may help explain Price, from
the following three: â??Ageâ?, â??Mileageâ?, or â??Weightâ? of a car. In the space below, state your
choice and explain why you chose it.
A car’s milometer is the measure of how long does the car life, it’s
lived. For example, a car with only 50,000 miles would worth more
than a car with 160,000 miles. So, a car with too many miles is much
better than one with less miles. It would cost a better cost if we sold
it with less mileage this is mean that car didnâ??t use a lot and
problems on the car would be less than a car was used so much.
2. Randomly select a subset (sample) of 100 observations from the data file using the
commands: Tables â?? Subset â?? Random – sample size: â?? (select 100 observations). After
doing so, please use the newly created data window, and move on to the Data Exploration
section below.
Data Exploration
3. Explore the dependent variable (Price) and independent variable visually, by creating
histograms for each one. Paste them below. Under each histogram, note the mean, say
whether the data is skewed, and note if there are any outliers.
The mean for price is 10251.5, it skewed to right, and there are outliers.
The mean for mileage is 71208.2, it skewed to right, and there are outliers
4. Write down the 95% confidence interval for the mean, for both the dependent and
independent variable.
5. For the Price variable, test the hypothesis of µ being different than 11,500 at the 5%
level of significance:
(a) State your null and alternative hypotheses.
H0=11,500
Ha â? 11,500
(b) Find the relevant p-value and write it down.
p>|t|=test statistic
p>= -4.0366
0.0001*2=0.0002
(c) What do you conclude, based on your findings?
I would conclude that we reject the null (H0) as P is less than 0.5%, and we
accept the alternative hypotheses (Ha). µ¹11,500.
6. Using Analyze â?? Fit Y by X, create a scatterplot between Price (Y) and the independent
variable (X) you chose. Paste it below, and comment on the following 4 concepts:
direction, shape, strength of relationship, and whether there are any outliers.
Direction: Left to right
Shape: Curvilinear
strength of relationship: Weak negative relationship.
Yes, there are outliers
7. Using Analyze â?? Fit Y by X, find what the correlation is between the two variables and
write it down. Then, comment on the strength of the relationship.
There is no relationship between the two variables, the correlation is close to 0.
Correlation= -0.55123
Simple Linear Regression Modeling
8. Fit the regression model:
(a) Run the regression of X (independent variable) on Y (Price), and plot the
regression line over the data. Paste your output below.
(b) Identify the results of the hypothesis test (p-value) on the regression slope
coefficient. What do you conclude?
P- Value < .0001. We conclude that we reject the null (Ho). (c) Write down the regression equation, by hand. Price = intercept - mileage * mileage Price = 13195.568 - (-0.041345) * mileage (d) Make a prediction for Y (Price), by using one of the relevant bullets below: â?¢ â?¢ â?¢ If your X variable for the project is Age, use 15 for X If your X variable for the project is Mileage, use 25,000 for X If your X variable for the project is Weight, use 1,200 for X Price = 13195.568- ((-0.041345) * 25,000) = 13195.568- (-1033.625) = 14229.193 ... Purchase answer to see full attachment

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