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- The Equal Opportunity Commission is investigating questions around unequal pay rates and discriminatory remuneration in various industries. The Pay Equity tab in the excel workbook contains information on 100 employees from a particular industry. Information includes: Salary ($) Gender Years of Education Years of Experience Division of employment Age Run a multiple regression analysis looking at the relationship between salary and years of education and years of experience. What proportion of variation in salary can be explained by these two variables? Conduct a test of the overall significance of the model. Test both the Education and Experience variables separately. Do both contribute to explaining the variation in salaries? Write out the estimated equation and interpret all coefficients. Salary (in $) Education (years) Experience (years) 20860 11 4 30200 16 1 31240 12 1 36860 12 8 44760 14 4 46690 19 3 47400 15 1 47880 14 3 50620 13 6 50690 14 4…Fixed effects regression is a method for controlling for omitted variables in panel data when the omitted variables do not vary across entities (states) but change over time. Fixed effects regression can be used when there are two or more than two time periods for each entity. Is this true or false? Provide an explanationSecretary performance The AFL-CIO has undertakena study of 30 secretaries’ yearly salaries (in thousands ofdollars). The organization wants to predict salaries fromseveral other variables.The variables considered to be potential predictors ofsalary areX1 = months of serviceX2 = years of educationX3 = score on standardized testX4 = words per minute (wpm) typing speedX5 = ability to take dictation in words per minuteA multiple regression model with all five variables was runon a computer package, resulting in the following output:Variable Coefficient Std. Error t-ValueIntercept 9.788 0.377 25.960X1 0.110 0.019 5.178X2 0.053 0.038 1.369X3 0.071 0.064 1.119X4 0.004 0.307 0.013X5 0.065 0.038 1.734s = 0.430 R2 = 0.863Assume that the residual plots show no violations of theconditions for using a linear regression model.a) What is the regression equation? b) From this model, what is the predicted Salary (in thou-sands of dollars) of a secretary with 10 years (120 months) of experience, 9th…
- Jadual 2 : Ringkasan analisis korelasi kajian kemurungan dan kebimbangan Table 2 : The summary of correlational analysis of depression and anxiety . Correlations Depression Anxiety Pearson Correlation Depression Anxiety Sig (2-tailed) Depression Anxiety N Depression Anxiety 1.00 .282 - .003 112 112 .282 1.00 .003 - 112 112 Based on this position, write the likely regression equation. Write down statistics representation of the correlation in APA format.You plan to fit a regression model that will be used to predict first-year college GPA (FYGPA) from high-school GPA (HSGPA), ACT score (ACT), first-generation status (Yes or No), socioeconomic class (lower class, lower to middle class, middle to upper class, and upper class), and school type (public or private). What is the total number of estimated regression coefficients? If the sample size is n = 250 students, what are the degrees of freedom for the following sources of variation: Regression Error TotalDefine Internal and External Validity When the Regression Is Used for Forecasting?
- What is the equation of the estimated population regression line? Group of answer choices Predicted Sale amount = 56.957 + 0.127*Tip Predicted Tip = 56.957 + 0.127*Sale amount Predicted Tip = 0.127 + 56.957*Sale amount Predicted Tip = 0.127 – 56.957*Sale amount Predicted Sale amount = 0.127 – 56.957*Tip Predicted Tip = 56.957 – 0.127*Sale amount Predicted Sale amount = 56.957 – 0.127*Tip Predicted Sale amount = 0.127 + 56.957*TipPredicting Percent Body FatThis problem uses the dataset BodyFat, which gives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (in pounds), Height (in inches), and circumference (in cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist.1Using Neck Circumference to Predict Body FatThe regression line for predicting body fat percent using neck circumference is BodyFat^=-47.9+1.75(Neck). Click here for the dataset associated with this question. (a) What body fat percent does the line predict for a person with a neck circumference of 35 cm?Round your answer to two decimal places.BodyFat^= %What body fat percent does the line predict for a person with a neck circumference of 40 cm?Round your answer to one decimal place.BodyFat^= % (b) One of the men in the study had a neck circumference of 38.7 cm and a body fat percent of 11.3. Find the residual for this man.Round your answer to three decimal places.residual= %…Correlation studies are designed to minimize other possible explanations and conclude a causal relationship between two measured variables? True or false
- Explain role of the instrument relevance condition in IV regression?wo thousand (2,000) adults ages 50 to 80 years were recruited into a 10-year prospective cohort study which started in 1971. The purpose of the study was to examine the effect of gender on death at the end of the study (died during the study period vs survived), controlling for age, years if smoking, and occupation. What is the most appropriate statistical analysis you would conduct to answer the research question? A. Multiple linear regression B. Survival analysisC. Multiple logistic regression.D. All of the aboveWhat is the variable of interest in this data set and what is the type of this variable?