# Project #72399 - Project 2 Stats

Statistics XL10: Project 2 Spring 2015, UCLA

Using any data of interest to your group, compile a data set comprised of one predictor and one response variable with at least 20 observations (data points), and answer the questions below. Your project needs to be typed and plots can be made using any software of your choice. Only one project (with each member’s name) per group needs to be submitted. Your project should include all the observations used.

Provide a brief description of your project. Make sure to identify the predictor and response variables, as well as discussing the objective of your regression model.

Note: All your answers must be in the order in which the questions are asked, otherwise you will be deducted 20%. Note: Even if only one answer is out of order you will still be deducted 20%.

1. (15%) For your predictor and response variables:

(a) compute the range and IQR. (b) make a histogram of your data.

(c) make a boxplot of your data.
2. (25%) Make a scatterplot of your data and describe the:

(a) Direction (b) Form

(c) Strength (d) Correlation

(e) Outliers

3. (60%) Based on your data, construct a linear regression model of your response variable as a function of your predictor variable following the steps below:

1. (a)  Compute x Ì„ and y Ì„

2. (b)  Compute sx and sy

3. (c)  Compute r

4. (d)  Compute a and b

5. (e)  Construct the respective Least Squares line and plot it over your scatter plot.

6. (f)  Compute the respective R2 and interpret your results.

7. (g)  For your model, compute and plot the residuals vs x. Describe what you observe from this plot.

8. (h)  Are there any outliers? If so, are they high leverage and/or influential.

9. (i)  Based on your model, make 3 predictions for your response variable (i.e., use 3 different values of x that are not in your data, and compute the respective y value).

 Subject Mathematics Due By (Pacific Time) 05/29/2015 11:00 pm
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