Good evening! I am enrolled in BUS 308, Statistics for Managers and I am having a difficult time with my homework. 

Week 4 : Identifying relationships – correlations and regression*To Ensure full credit for each question , you need to show how you got your results . This involves either showing where the data you used is located*or showing the excel formula in each cell .Be sure to copy the appropriate data columns from the data tab to the right for your use this weekWhat is the correlation between and among the intervaliratio level variables with salary ? [Do not include compa- ratio in this question .* !*a Create the correlation table .*What is the data input ranged used for this question :"Use Cell KO8 for the Excel test outcome location .in . Create a correlation table in cell Kog .6. Technically , we should perform a hypothesis testing on each correlation to determineif it is significant or not . However , we can be faithful to the process and save some*time by finding the minimum correlation that would result in a two tail rejection of the null*We can then compare each correlation to this value , and those exceeding it ( in either apositive or negative direction ) can be considered statistically significant .i . WThat is the t-value we would use to cut off the two tails ?= Iin What is the associated correlation value related to this t-value ? * =C. What variable( s ) is ( are ) significantly correlated to salary ?d. Are there any surprises – correlations you though would be significant and are not , or non significant correlations you thought would be ?e. Why does or does not this information help answer our equal pay question ?*Perform a regression analysis using salary as the dependent variable and the variables used in Q 1 along with*our two dummy variables – gender and education . Show the result , and interpret your findings by answering the Following questions .Suggestion : Add the dummy variables values to the right of the last data columns used for 2 1 ." That is the multiple regression equation predicting ; explaining salary using all of our possible variables except compa-ratio ?*That is the data input ranged used for this question :`6 .Step 1 : State the appropriate hypothesis statements :"Use Cell M1 3 4 for the Excel test outcome locationHO:Ha :step 2 : Significance ( Alpha )Step 3 : Test Statistic and test !Why this test ?`Step 4 : Decision rule .*Step 5 : Conduct the test – place test function in cell M13 4Step 6 : Conclusion and Interpretation*What is the p – value ."What is your decision : RE.J or NOT reject the null ?Why ?What is your conclusion about the factors influencing*the population salary values?"If we rejected the null hypothesis , we need to test the significance of each of the variable coefficients .*Step 1 : State the appropriate coefficient hypothesis statements .*( Write a single pair , we will use it for each variable separately . )HO :Ha :Step 2: Significance ( Alpha )`Step 3 : Test Statistic and tesWhy this test ?*Step 4 : Decision rule :*Step 5 : Conduct the testNote , in this case the test has been performed and is part of the Regression output above .Step 6: Conclusion and InterpretationPlace the t and p- values in the following tableIdentify your decision on rejecting the null for each Variable . If you reject the null , place the coefficient in the table ."Midpoint_Perf. Rat. Seniority_ Raise_Gender*_ Degree`L- Value:\-value .Rejection Decision" I Null is rejected , what is thevariable’s coefficient value ? !ITsing the intercept coefficient and only the significant variables , what is the equation ?*Salary =Is gender a significant factor in salary ?Regardless of statistical significance , who gets paid more with all other things being equal ?*How do we know ?*After considering the compa- ratio based results in the lectures and Your salary based results , what else would you like to know*before answering our question on equal pay ? Why ?`Between the lecture results and You’r results , What is your answer to the question*of equal pay for equal work for males and fernales ? Why ?`What does regression analysis show us about analyzing complex measures ?