write the regression formula for this in STATA
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write the regression formula for this in STATA?
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- What does the correlation matrix for a multiple regression analysis contain?A. Multiple correlation coefficientsB. Simple correlation coefficientsC. Multiple coefficients of determinationD. Multiple standard errors of estimateWhat is the odds ratio for a study with a logistic regression coefficient of -0.2524? a) 0.78 b) 1.00 c) -0.78 d) -2524Statistical technique used to determine the degree to which two variables are related is known as a. Regression b. Correlation c. None of these d. Dispersion
- The Student's t distribution table gives critical values for the Student's t distribution. Use an appropriate d.f. as the row header. For a right-tailed test, the column header is the value of α found in the one-tail area row. For a left-tailed test, the column header is the value of α found in the one-tail area row, but you must change the sign of the critical value t to −t. For a two-tailed test, the column header is the value of α from the two-tail area row. The critical values are the ±t values shown. A random sample of 46 adult coyotes in a region of northern Minnesota showed the average age to be x = 2.11 years, with sample standard deviation s = 0.77 years. However, it is thought that the overall population mean age of coyotes is μ = 1.75. Do the sample data indicate that coyotes in this region of northern Minnesota tend to live longer than the average of 1.75 years? Use α = 0.01. Solve the problem using the critical region method of testing (i.e., traditional method). (Round…The beta of a stock has been estimated as 1.4 using regression analysis on a sample of historical returns. A commonly-used adjustment technique would provide an adjusted beta of A. 1.32. B. 1.13. C. 1.0. D. 1.27.The statistic used to test whether individual regression coefficients are different from zero in the population is: Select one: a. F O b. b Oc. R2 O d. t Clear my choice
- The table below shows the average temperature in New York City (NYC), measured in degrees Fahrenheit (°F), where January is month 1, February is month 2, etc. Jul Jan 38.8 21.3 59.2 Using the regression, the average annual temperature in NYC is predicted to be 58.4 Jun Aug Oct Nov Feb Mar Apr 40.5 47.3 56.8 Sep 72.7 62.4 53.2 76.8 80.1 The data above can be modelled by an equation in the form y = a sin (bx+c) + d. 60.0 Ma 68.4 sin Dec 43.0An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.12 A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.531 b=23.45 r2=0.378225 r=0.615 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole numbe
- A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: ??=?+????+????+???? Where FR = yearly foreign reserves ($000’s), OIL = annual oil prices, EXP = yearly total exports ($000’s) and FDI = annual foreign direct investment ($000’s). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 * 0.0057 FDI -396.99 160.66 -2.471 ** S = 2.45 R-sq = 96.3% R-sq(adj) = 95.3%…Longevities of archbishops and monarchs 15 Archbishops 17 16 15 18 16 19 12 15 13 12 12 13 15 14 18 14 10 17 13 16 15 Monarchs 17 17 13 14 20 19 21 15 17 18 17 18 Print DoneIn running a logistic regression, a statistician decided to include decade of life (20s, 30s, 40s, 50s, 60s) as a categorical variable in the systematic component because they didn't believe the relationship between the log-odds and age was linear. Using dummy variables to create the systematic component, how many dummy variables would be needed to represented age?