A disease characterized by muscle tremors and rigidity and sometimes dementia is called:

A relationship based on trust and confidence, that provides comfort and reassurance, and enables independence is a ______________ relationship.

A persons sex refers to _________________, whereas a person’s gender refers to:

The ________ stage of Alzheimer’s involves irritability, paranoia, little or no communication, a lack of recognition of loved ones.

A recent survey of the clerical employees of a large financial organization included questions related to employee satisfaction with their supervisors.  Data were generated from the individual employee response to the items on the survey questionnaire.The data were collected in 30 departments selected at random from the organization  (top 5 values shown below). The resulting data consist of 30 observations on seven variables, one observation for each department. Department_ID Job_Satisfaction Supervisor_Support Workload_Fairness Compensation_Satisfaction Work_Life_Balance Career_Growth Overall_Satisfaction 1 3.8 4.1 3.8 3.2 4.6 4.8 3.7 2 3.2 3.3 3.5 4.4 4.8 3.5 3.2 3 4.5 4.6 4.7 4.5 3.6 3.3 4.8 4 4.3 4.9 3.7 4.1 3.2 4 4.8 5 3.4 3.3 3.6 4.5 3.5 5 3.5 Analysis of Variance Source DF Adj SS Adj MS F-Value P-Value Regression 5 11.7432 2.34865 130.65 0.000 Job_Satisfaction 1 0.0285 0.02848 1.58 0.220 Supervisor_Support 1 1.1477 1.14773 63.85 0.000 Workload_Fairness 1 0.1118 0.11176 6.22 0.020 Compensation_Satisfaction 1 0.1077 0.10768 5.99 0.022 Work_Life_Balance 1 0.0001 0.00015 0.01 0.929 Error 24 0.4314 0.01798     Total 29 12.1747     Refer to the ANOVA table above to select an appropriate set of hypotheses statements that correspond to the F-test.

A data set from a study of 57 female college athletes shows a response variable  max BP  =  maximum   bench press that has explanatory variable    BP60  =  number   of repetitions before fatigue with a​ 60-pound bench press. Some results of regression analysis are given​ below. Picture14png.png Picture1(1)(1).png  Examine the residual plots shown above. What do they​ describe? What do they​ suggest?

A financial analyst developed the following multiple regression model to predict the monthly return on a stock (y) based on three predictors: the return on the S&P 500 index ( x 1 x_1 ​), the monthly interest rate ( x 2 x_2 ​), and the company’s monthly revenue growth percentage ( x 3 x_3 ​): y ^ = − 0.5 + 1.2 x 1 − 0.8 x 2 + 0.4 x 3 \hat{y} = -0.5 + 1.2x_1 – 0.8x_2 + 0.4x_3 ​ Which of the following best describes the interpretation of the coefficient for x 2 x_2 ​ (monthly interest rate)?

A researcher found a significant relationship between a​ student’s IQ, x​, and their​ score, y, on the verbal section of the SAT test. The relationship can be represented by the regression equation  y ^ = 225 + 1 . 15 x . What is the estimated slope?

For a random sample of children from a school district in South​ Carolina, a regression analysis is conducted of y=   amount spent on clothes in the past year​ (dollars) and x=year in school. Software reports the tabulated results for observations at x=12. Predicted Values for New Observations NewObs Fit SEFit ​95% CI ​95% PI 1 448.0 10.6 ​(427,469) ​(101,795) Interpret the value listed under​ “95% PI”. Choose the correct answer below.

A recent survey of the clerical employees of a large financial organization included questions related to employee satisfaction with their supervisors.  Data were generated from the individual employee response to the items on the survey questionnaire.The data were collected in 30 departments selected at random from the organization  (top 5 values shown below). The resulting data consist of 30 observations on seven variables, one observation for each department. Department_ID Job_Satisfaction Supervisor_Support Workload_Fairness Compensation_Satisfaction Work_Life_Balance Career_Growth Overall_Satisfaction 1 3.8 4.1 3.8 3.2 4.6 4.8 3.7 2 3.2 3.3 3.5 4.4 4.8 3.5 3.2 3 4.5 4.6 4.7 4.5 3.6 3.3 4.8 4 4.3 4.9 3.7 4.1 3.2 4 4.8 5 3.4 3.3 3.6 4.5 3.5 5 3.5 Regression Equation Overall_Satisfaction = -1.027 + 0.143 Job_Satisfaction + 0.866 Supervisor_Support + 0.1207 Workload_Fairness + 0.1214 Compensation_Satisfaction – 0.0039 Work_Life_Balance Coefficients Term Coef SE Coef T-Value P-Value VIF Constant -1.027 0.430 -2.39 0.025   Job_Satisfaction 0.143 0.114 1.26 0.220 7.85 Supervisor_Support 0.866 0.108 7.99 0.000 9.02 Workload_Fairness 0.1207 0.0484 2.49 0.020 1.37 Compensation_Satisfaction 0.1214 0.0496 2.45 0.022 1.32 Work_Life_Balance -0.0039 0.0430 -0.09 0.929 1.03 Model Summary S R-sq R-sq(adj) R-sq(pred) 0.134075 96.46% 95.72% 94.64% Refer to the tables above to check if the “workload fairness” is a significant predictor for employee satisfaction. Use a significance level of 5%.