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STAT 1000Q Lecture Notes - Lecture 18: Scania N112

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19 Oct 2017

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Robert Apruzese

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STAT 1000Q Full Course Notes

STAT 1000Q Full Course Notes

Document Summary

Statistic notes 1000q- lecture #18-t-tests and z-tests for pop proportions. For t-tests, we need to find a sigma to use since it is unknown. To compute p-value: use area under t-distribution graph. For a right tailed test, the p-value is the area to the right of t. For a left tiles t-est, the p-value is the area to the left. For two tailed test, double the right-tailed formula. Due to symmetry, p-value= 2 x tcdf(t, 10^99, n-1) The volatility of a stock is the beta coefficient (x) X=1: stock has risk compared to the market. X>1: stock has more risk than market as a whole. X<1: stock has less risk than the market as a whole. N=10, mean beta coefficient= x bar= 1. 23. Assume normal with rejection level of 0. 10. T= (1. 23-(cid:1005)(cid:895) / (cid:1004). (cid:1007)(cid:1011) x (cid:1005)(cid:1004) = (cid:1005). (cid:1013)(cid:1010)(cid:1010)

Related textbook solutions

Introductory Statistics

OER Edition, 2013

ISBN: 9781938168208

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Related Questions

Use the following scenario for questions 6 – 8. In 2016-17, the average SAT score of the UVA first year class was 1420 out of 1600. An advisor in the statistics department is interested in determining whether statistics majors from that class have higher SAT scores than the average. He tests H,:µ = 1420 against Hạ: µ > 1420, where u is the mean SAT score for statistics majors from the 2016-17 first year class. In a simple random sample of 30 statistics majors, he finds a sample mean SAT score of 1440 with sample standard deviation of 40.

6. What is the value of the test statistic for this significance test?

a. 0.09

b. 0.5

c. 2.73

d. 20

7. From what distribution is this test statistic?

a. N(0, 1)

b. N(1420, 7.30)

c. t distribution with 29 degrees of freedom

d. t distribution with 28 degrees of freedom

8.) The p-value for this test is 0.005. Which of the following is a proper interpretation of this p- value?

a.There is a 0.5% chance that the null hypothesis is true.

b. If the population mean SAT score really is 1420, there's a 0.5% chance that the sample a. mean SAT score from 30 statistics majors would equal 1440.

c.If the population mean SAT score really is 1420, there's a 0.5% chance that the sample mean SAT score from 30 statistics majors would be 1440 or lower.

d. If the population mean SAT score really is 1420, there's a 0.5% chance that the sample mean SAT score from 30 statistics majors would be 1440 or higher.

2. (12 marks) In a study of 85 individuals, food questionnaires were used to measure the change in polyunsaturated fatty acids (PUFA) intake from the beginning to the end of the study. In addition researchers measured a genetic marker in the TNF-αgene; for this analysis, we will take the two values of this TNF-αvariable to be A- or A+. The researchers also collected information on gender, age and BMI. The primary question of interest is whether TNF-αmodiﬁes the eﬀect of PUFA on HDL.

(a) (1 mark) Let TNFa be a variable with value 1 for A+ and 0 for A- TNF-αstatus and

let gender be 1 for males and 0 for females. State a linear model for mean change in HDL that includes the predictors PUFA, TNFa, PUFA×TNFa interaction, and eﬀects for gender, age and BMI.

(b) (1 mark) A summary of the ﬁtted model is:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 0.037531 0.196980 0.191 0.8494

pufa 0.019143 0.009245 2.071 0.0417

TNFa 0.074433 0.034128 2.181 0.0322

gender -0.008988 0.031793 -0.283 0.7781

age -0.003895 0.002156 -1.806 0.0747

bmi 0.006777 0.004332 1.565 0.1217

pufa:TNFa -0.024575 0.017844 -1.377 0.1724

Write a short sentence to describe why we would even consider removing gender from the model (i.e., why we would not just be happy with the above model from

(c) (2 marks) Below is a summary of the model ﬁt without gender. Using our 10% rule-of-thumb, is there any evidence that gender confounds the PUFA×TNFa eﬀect?

If so why, if not why not?

Estimate Std. Error t value Pr(>|t|)

(Intercept) 0.024467 0.190364 0.129 0.8981

pufa 0.018841 0.009130 2.064 0.0423

TNFa 0.074850 0.033897 2.208 0.0301

age -0.003783 0.002107 -1.795 0.0765

bmi 0.006835 0.004301 1.589 0.1161

pufa:TNFa -0.024496 0.017737 -1.381 0.1712

(d) (2 marks) The researchers decided to use the model with PUFA, TNFa, PUFA×TNFa, age and BMI for inference of PUFA×TNFa interaction. What are the degrees of

freedom for the t-distribution whose critical value we need to construct conﬁdence intervals for the interaction? What upper tail probability should you use for a 95%

conﬁdence interval?

(e) (1 mark) The appropriate critical value is 1.96. Construct a 95% conﬁdence interval for the interaction.

(f) (2 marks) State the null hypothesis and a two-sided alternative hypothesis for testing whether TNFa modiﬁes the eﬀect of PUFA on HDL.

(g) (1 mark) From the computer output, what is the p-value for this test?

(h) (2 marks) For ﬁxed age and BMI, what is the estimated eﬀect of a one-unit change in PUFA for a subject who is A- at TNF-α? For ﬁxed age and BMI, what is the estimated eﬀect of a one-unit change in PUFA for a subject who is A+ at TNF-α.

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(14 marks) Fortune magazine publishes a list of the world’s billionaires each year. We will examine the top 97 of the 1992 list. Their wealth, age, and geographic location (Asia, Europe, Middle East, United States, and Other) are reported. Wealth is a right-skewed variable, so we will consider the natural logarithm log wealth to be the response and will see if age and geographic location are predictors.

(a) (2 marks) Let

Ebe a variable that is 1 if the person is from Europe and 0 otherwise,

Mbe a variable that is 1 if the person is from the Middle East and 0 otherwise,

Obe a variable that is 1 if the person is from the “Other” region and 0 otherwise,

Ube a variable that is 1 if the person is from the United States and 0 otherwise.

State a linear model for the mean of log wealth that includes age and the above 4

geographic variables. Call this the full model.

(b) (5 marks) The SSY for these data is 28.3351 and the SSE from ﬁtting the full model

is 27.0461. Use this information to construct an ANOVA table. Your table should

include columns for Source, df, SS, MS and F, and should include rows for the model

(full model), residual and total.

(c) (2 marks) In addition to the full model, the reduced model that includes only an

intercept and age is ﬁt. What is the null hypothesis being considered by ﬁtting these

two models? (Refer to quantities deﬁned in your model.)

(d) (3 marks) The SSM from the reduced model is 59.7. Calculate an F-statistic to test the hypothesis of part (c). State the degrees of freedom for the F-distribution

you would compare this statistic to. (You do not need to calculate the p-value or actually test the hypothesis.)

(e) (1 mark) Using terminology from class, name the kind of Ftest that the statistic in part (d) corresponds to.

(f) (1 mark) If the null model for these data is compared to the model that includes an

intercept and age, what are the results?

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