Always get overwhelmed by the amount of material when covered at a comprehensive level. Attached is the study material of what to be prepared to cover at the conclusion of this course. I have worked through them but get stumped at several points. Can you provide a systematic approach to these problems and provide a reference to refer to make sure my solutions are accurate. It would helpful if you can explain why you did what you did, as this is just a helpful of study and questions may appear differently at the actual conclusion of the course.

An accountant wishes to predict direct labor cost (y) on the basis of branch size (x) of a product produced in a job shop. A sample of 14 production runs revealed the following:
Refer to Table 11A on the Handout for MegaStat output.
Part A
Analyze the above output to determine the regression equation.
Part B
What conclusions are possible using the meaning of b0 (intercept) and b1 (size) in this problem? (That is, explain the meaning of the coefficients)
Part C
What conclusions are possible using the coefficient of determination (-sqaured)?
Part D
Calculate the coefficient of correlation. Interpret this value.
Part E
Does this data provide significant evidence (alpha=0.05) that the direct labor costs are associated with the size of a batch? Find the p-value and interpret.
Part F
Predict the average direct labor cost for a batch size of 100.
Part G
What is the 95% confidence interval for the direct labor cost for a batch size of 100. What conclusion is possible using this interval?

Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.

Perform Regressionanalysis
(1)
A ($3.76, $3.80)?
B ($3.87, $3.89)?
C ($3.85, $3.84)?
(2)
A ($3.87, $3.89)?
B ($3.91, $3.93)?
C ($3.95, $4.29)?
(3)
A ($3.98, $3.99)?
B ($4.03, $4.05)?
C ($3.99, $4.05)?
[Please the attached questions file].

Describe some data that you would not want to use regressionanalysis on. How could you test and make sure you have the right data before proceeding with the analysis?

Correlation and RegressionAnalysis of students when it is best to determine "appropriate" variables and to make calculations. This means that you will have to determine which variable(s) you feel are best and why and answer each of six questions 100% as well as present appropriate statistical graphs or charts. Please see attach

In regressionanalysis, the omission of one or more significant explanatory variables from the regression equation constitutes:
a multicollinearity
b autocorrelation
c specification error
d heteroscedasticity
e none of the above

The following data show the annual revenue ($millions) and the estimated team value ($millions) for the 32 teams in the National Football League (Forbes website, February 2009). Please use Excel.file attached.
Answer the following:
1. Write the regression equation,
2. Interpret the regression constant and regressi

1)Given the regression equation: Y = 1.3479 + 0.3978 X, what is the fitted value (orY ? ) if X = -3?
2) Calculate bo, b1 for the information provide below
X Y
-2 9
0 5
-0.5 7
1 100

1. Compute the Pearson correlation for the following data.
X Y
7 3
3 1
6 5
4 4
5 2
2. Find the regression equation for predicting X from Y for the following set of scores.
X Y
0 9
1 7
2 11

Please make up a simple regressionanalysis "application" example.
For the "application" example submit both your manual and excel stats functional work for testing hypothesis H0: beta 1=0 (by using t test).
A typical simple regressionanalysis "application" example is as follows: The following data are the height, in inches,