1. Two groups of 15 plants were grown under the same controlled conditions, but each group was treated with a different fertilizer. The results for the differences in plant size are: Ed =314, Ed^2=26513.38. At a 2% significance level, is there a significant difference between the fertilizers?

2. A sample of 94 students at a community college was taken to determine information about commuting distances to school. Sixty-four students reported commuting distances of more than 5 miles. Determine the 95% confidence interval for the proportion of students,p, who commute more than 5 miles?

3. The director of human resources in a corporation believes that the distribution of education levels among new employees is the same as among new hires two years ago. The distributions are as follows:

Distribution two years ago

Education level/Percent
High School -25.7%
College 2 years - 29.5%
College 4 years - 37.0%
Graduate - 7.8%

Distribution this year

Education level/Observed
High School - 18
College 2 years - 49
College 4 years - 48
Graduate - 13

Test the hypothesis at a 10% significance level.

4. Given the following statistics:
Ex=270, Ey=3023, Exy=94,123, Ex2= 8316, n=9, SST=79,444.9, SSR=54,562.4,
SSE= 24,882.5

a. Find the regression equation
b. Compute the coefficient of determination
c. Compute the correlation coefficient
d. Comment on the usefulness of the regression to make predictions

5. Perform the correlation test:
H0: p=0
Ha: p not equal to 0
at the 5% significance level, given n=11 and r= -0.331

Solution Summary

5 hypothesis testing questions covering these topics are worked out and explained in an attached .doc file.

Please help with the following problem.
Using the data on the table below, are there any correlations between population changes for the areas listed.
The following is a list of acceptable tests:
regression line and equation; correlation
one-sample t-test
one-sample t confidence interval
matched-pairs t-test
two-sa

Module 6: Correlation and Regression
A For the supermodel dataset at the right, treat height as the explanatory variable and weight as the response variable. (Data set is given in the excel file)
1 Is there a significantcorrelation? Show the null hypothesis, df and the test you used.
yes/

Suppose a regression output produces the following 99% confidence interval for one regression coefficients: [-32.47,-16.88]
Given this information, should an analyst reject the null hypothesis that this population regression coefficient is equal to 0? Explain your answer.

Regression:
Using the height and weight of five people as listed below.
Height (inches) 67 66 66 62 63
Weight 148 173 131 123 115
Step 1: Calculate correlation coefficient (r) between height and weight.
Step 2: Determine if a significant linear correlation exists between height and weight.
Step 3: Find predicted valu

Please use data of the attached two tables to answer the following questions about Pb 9.24.
C) Find the regression coefficiet a and b.
K)iii. Construct the 99% confidence interval for ?.
I)iii. Construct the 99% confidence interval for ?.
(p) Compute the correlation coefficient r.
q)ii. Construct the 95% confidence i

1. An auto manufacturing company wanted to investigate how the price of one of its car models depreciates with age. The research department at the company took a sample of eight cars of this model and collected the following information on the ages (in years) and prices (in hundreds of dollars) of these cars.
Age (x) 8 3 6 9

Try out some of your own ideas for analyzing
this data. Use one of the following techniques:
regression line and equation; correlation
one-sample t-test
one-sample t confidence interval
matched-pairs t-test
two-sample t-test
two-sample t confidence interval
F-test for variances
ANOVA
one-sample z test for proportions

1 What is the R^2 Value for your regression equation?
2 What is the value of the coefficient of Blue Collar in your equation?
3 What is the lower limit of the 95% CI for this coefficient?
4 What is the upper limit of the 95% CI for this coefficient?

Dear OTA,
Can you please assist me with this? Please see the attached file.
Thanks
You are given the following summary statistics from a regression analysis:
ŷ = 200 + 150x
SSE = 25.25
_
SSX = Sum of squares X = (x -x) 2 = 99.645
n = 18
_

QUESTIONS:
(a) How does correlation analysis differ from regression analysis?
(b) What does a correlation coefficient reveal?
(c) State the quick rule for a significantcorrelation and explain its limitations.
(d) What sums are needed to calculate a correlation coefficient?
(e) What are the two ways of testing a correlati