We are interested in the relationship between mid-term exam scores and final exam scores. The Final Exam score is the dependent variable and Midtermscore is the independent variable. Use the simple regression output on below to answer the question below. Use a significance level of 0.05 for allhypothesis tests and intervals.A point estimate for the Final Exam score for a student with a score of 85 on the Midterm?O Bivariate Fit of Final Exam By Midterm1009080706050556065707580859095100MidtermParameter EstimatesTermEstimate Std Error t Ratio Prob>|t| Lower 95% Upper 95%0.0031*<.0001*11.1665220.36150443.09Intercept 31.738559 10.26099Midterm52.3105960.61916 0.1285144.820.8768157Upper 95%Indiv Final ...PredictedLower 95%Upper 95%Lower 95%Student Midterm Final ExamFinal ExamMean Final ... Mean Final ..Indiv Final ...7075.07976245 71.391337991 78.768186908 53.411179985 96.748344914Final Exam

For the given data given midterm = 85 then Final exam score =?

Answered: We are interested in the relationship…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
A researcher wants to forecast the annual sales of Walmart, based on store size. To examine the relationship between the store size in square feet and its annual sales in million dollars, a sample of 14 stores was selected shown below in the image: Answer the following: i) Null hypothesis of correlation ii) Coefficient of Correlation and its interpretation iii) Interpret the sig value of ANOVA. iv) Coefficient of Determination and its interpretation v) Write down the Regression Model. vi) Interpret the value of ‘a’ vii) Interpret the value of ‘slope’
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: What is the sample estimates of the regression problem? Which of the independent variables in the model are significant at the 5% level? Formulate the hypothesis and explain the answer.
TAMU admissions board believes the score you get on the SAT in high school can help predict your college GPA. Below is a regression model using the SAT scores and GPA for 83 college graduates. Calculate a 70% Confidence Interval for the slope of the regression line. Use 4 decimal places.(Note: The SAT scores have been divided by 100 just to make the numbers nicer) Simple linear regression results:Dependent Variable: GPAIndependent Variable: SAT/100GPA = 1.318967 + 0.174653 [SAT/100]Sample size: 83R (correlation coefficient) = 0.1487R-sq = 0.0221Estimate of error standard deviation: 0.118302Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 1.318967 0.3631 81 3.633 0.00049 Slope 0.174653 0.129086 81 1.353 0.1798 Use 4 decimal places
The systolic blood pressure dataset (in the third sheet of the spreadsheet linked above) contains the systolic blood pressure and age of 30 randomly selected patients in a medical facility. What is the equation for the least square regression line where the independent or predictor variable is age and the dependent or response variable is systolic blood pressure? Y=__________ X + ______________ Patient 7 is 67 years old and has a systolic blood pressure of 170 mm Hg. What is the residual? __________ mm Hg Is the actual value above, below, or on the line? What is the interpretation of the residual? (difference in actual &predicated bp, difference in age, the amount of systolic changes)
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
The attached results are for a multiple regression study of smartphone addiction (SSA-SV) proneness in relation to 1) Gender 2)Age 3) Anxiety (GAD-7). I just want to clarify what the F-statistic means and the effects of AGE on the F-statistic; given that AGE is statistically significant compared to the other predictor variables.
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: What is the population model of this regression problem? What is the sample estimates of the regression problem? Which of the independent variables in the model are significant at the 5% level? Formulate the hypothesis and explain the answer.
The General Aviation Manufacturers Association has reported annual flying hours and fuel consumption for airplanes with a single, piston-driven engine as listed in table below. Data are in millions of flying hours and millions of gallons of fuel, respectively. Determine the linear regression equation describing fuel consumption as a function of flying hours. At the 0.05 level of significance, could the population slope and the population coefficient of correlation be zero? Determine the 95% confidence interval for the population slope. Year Hours Gallons 1992 18400000 199100000 1993 17000000 184200000 1994 16400000 177200000 1995 17800000 192600000 1996 17600000 188400000 1997 18300000 196300000
The accompanying table lists systolic blood pressures (mm Hg) and diastolic blood pressures (mm Hg) of adult females. Find the (a) explained variation, (b) unexplained variation, and (c) prediction interval for a systolic blood pressure of 118 mm Hg using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Systolic Diastolic 127 69 103 65 130 73 104 64 157 74 97 51 155 90 111 69 124 68 112 75 103 60 128 67
Would someone familiar with SPSS be able to help me complete the table and the questions? (a) Explain which of the variables have statistically significant effects at the α = 0.05 level. (b) Are the conclusions different to the results obtained by univariate regression? Explain why and which approach is likely to be preferable?

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