Consider estimating the relationship between annual income (income) and a dummy variable equal to 1 if an individual is a female and 0otherwise gender by running an OLS regression in Stata. The results are in Figure 1.. reg income gender, robustLinear reg ressionNumber of obs4,779F(1, 4777)188.63Prob > F0.0000R-squared0.0394Root MSE36681RobustincomeCoefficient std. err.P>|t|[95% conf. interval]gender1082.5512033.434-13.730.000-16990.16-12745.57_cons21.180.00039072.1547045.09The OLS estimate of the intercept parameter is:a. -43,068.13212b. 955.0827С.The information given in the question is not sufficient to provide an answerd. 43,068.132129国0010W四0073NOVX22étv 0

Solution: Given informaton: n= 4779 observation. S.E(β0^)= 2033.434 Standard error of intercept t…

Answered: Consider estimating the relationship…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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: FR=a+B0IL+YEXP+8FDI 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% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 d) Hence test whether ß is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq“ and comment on its value.
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: Hence test whether ? is significant. Give reasons for your answer. Perform the F Test making sure to state the null and alternative hypothesis. Given an interpretation of the term “R-sq” and comment on its value.
4. A pharmaceutical company wants to test whether the incidence of side effects (i.e. adverse events)differs between the treatment and placebo groups at theα= 0.05. Letp1= the proportion of subjects in the treatment groups who experienced at least one adverse event and letp2= the proportion of subjects in the placebo group who experience at least one adverse event. 8 out of 30 people in the treatment group experienced at least one adverse event and 5 out of 30 people in the placebo group experienced at least one adverse event. (a) Set up the null and alternative hypothesis (using mathematical notation/numbers AND interpret them in the context of the problem) (b) Calculate the test statistic (c) Calculate the critical value (d) Draw a picture of the distribution of the test statistic under H0. Label and provide values for the critical value and the test statistic, and shade the critical region. (e) Make and justify a statistical decision at theα= 0.05 level and state your conclusions in…
Please do not explain, just say the answer like A,B,C,D,
Consider the accompanying data set of dependent and independent variables a. Perform a general stopwise regression using a 0.05 for the p-value to enter and to remove independent variables from the regression model b. Perform a residual analysis for the model developed in part a to verify that the regression conditions are met Click the icon to view the data a. Use technology to perform the general stepwise regression What is the resulting regression equation? Note that the coefficient is 0 for any variable that was removed or not significant -0.69 (050), (050)+(018) - X (Round to two decimal places as needed) • Data Table: y 63 43 51 49 40 42 23 37 30 27 20 31 FR 74 63 78 3534 52 44 47 35 17 15 20 17 Print X₂ 21 259. 15 9 38 18 17 5 40 27 30 33 x₂ 22 aadosa 2NNG 29 20 17 13 17 8 15 10 10 Done 1
The regression output is reported in Table 4. Why does Stata omit hhsize3? Would it make any difference if Stata omitted hhsize3 instead of hhsize1?
This table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…
An 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.
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: FR=a+BOIL+YEXP+8FDI Where FR = yearly foreign reserves (S000'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 ЕXP -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% Analysis of Variance Source DF MS F Regression 3 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values **', **", '?'and ??"
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: FR=a+B0IL+YEXP+8FDI 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% Analysis of Variance Source DF MS F Regression 1991.31 663.77 ?? Error 12 77.4 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation
Study conductes in patients with HIV. Primary outcome is CD4 coubt(measure stage of disease). Lower CD4=more advanced disease. Wqnt to find association between taking vitamins and supplements and CD4 count. Multiple regression analysis done relating CD4 to use of supplements (1=yes 0=no) and to duration of HIV in years. (# of yeara between diagnosis and study date) y=CD4 Count Y=501.41+12.67 supplements -30 23 duration of HIV. A. What is ezpected CD4 count for patients taking supplements who had HIv for 2.5 years? B. Expected CD4 count not takong supplements with HIv at study start date? C. Expected CD4 coubt for patients not taking supplements with HIV for 2.5 years? D. Uf compare 2 patients, 1 HIV for 5 years longer than other, whats expected difference in CD4 count?
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