5) The following results are from data where the dependent variable is SALARY, the independent variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0 for males. e) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above? f) Is the regression equation as a whole significant at the 1% level of significance? How do you know? g) What is the effect on the income of a person being a female versus male? h) Is there a significant amount of evidence (say at the 10% level of significance) that an additional year of education increases income by more than $2000? Be sure to state your null and alternative hypotheses, calculate your test statistic, and find the critical value.

5) The following results are from data where the dependent variable is SALARY, the independent variables are AGE, EDUCATION, and FEMALE which is a dummy variable = 1 for females and = 0 for males. e) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above? f) Is the regression equation as a whole significant at the 1% level of significance? How do you know? g) What is the effect on the income of a person being a female versus male? h) Is there a significant amount of evidence (say at the 10% level of significance) that an additional year of education increases income by more than $2000? Be sure to state your null and alternative hypotheses, calculate your test statistic, and find the critical value.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.3: Measures Of Spread

Problem 1GP

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The data set AIRQ contains observations for 30 standard metropolitan statistical areas (SMSAS) in California for 1972 on the following variables. indicator of air quality (The lower the better) value added of companies (in 1000 US$) amount of rain (in inches) dummy variable, 1 for (SMSAS) at the coast, 0 for others population density (per square mile) average income per head (in US$) airq vala rain сoas dens тedi reg airq vala rain coas dens medi df Number of obs 30 2.98 Source MS F( 5, Prob > F 24) = Model Residual 8723. 84625 14058.4538 1744.76925 0.0313 R-squared Adj R-squared = 0. 3829 0.2544 24.203 24 585.768906 Total 22782.3 29 785. 596552 Root MSE airq Coef. std. Err. P>|t| [95% Conf. Interval] vala rain 0. 699 .0008834 .2506988 -33. 3983 -.0010734 .0005545 0. 39 0.73 -3.19 -0. 66 0.65 .0055399 .9596857 -11. 81504 .0022562 -.0037731 -.458288 -54.98156 -.0044237 -.0012003 80. 29141 3435183 0.473 0. 004 0. 515 0. 521 сoas 10.45752 dens medi .0016233 .0022769 .0008503 .0023093…
The first graph is to deceleration measurements. Second is to variance. Please help I need in an hour thankyou.
Avalanches can be a real problem for travelers in the western United States and Canada. Slab avalanches studied in Canada had an average thickness of u = 67 cm. A sample of 31 avalanches in the U.S. gave a sample mean of = 63.0 cm. It is known that o = 10.3 cm for this type of data. Use a 0.03 level of significance to test the claim that the mean slab thickness of avalanches in the United States is different from that in Canada. Use the P-Value Approach. What is the P-Value for this problem? O 0.0154 0.0150 0.0300 0.0308
Avalanches can be a real problem for travelers in the western United States and Canada. Slab avalanches studied in Canada had an average thickness of u = 67 cm. A sample of 31 avalanches in the U.S. gave a sample mean of = 63.0 cm. It is known that o = 10.3 cm for this type of data. Use a 0.03 level of significance to test the claim that the mean slab thickness of avalanches in the United States is different from that in Canada. Use the P-Value Approach. What are the hypotheses for this problem? А: Но и 3D 63.0 ст us На и + 63.0 ст B: Но и 63.0 ст С: Но и %3D 67 ст us HA и < 67 ст D: Ho u = 67 cm vs HA H# 67 cm B O A
A health professional is whether stress level before a routine practice session can be used to predict the mean stress level a major figure skating competition. The health professional selected a random sample of figure skaters and measured the stress level before a routine practice session and before a major competitionEach variable was measured as the change in the interval between heartbeats , or heart rate variability . The health professional wants to estimate the mean change in the stress level before a major competition for each unit increase in the stress level before a routine practice.
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