In Exercises 5–20, assume that the two samples are independent simple random samples selected from
12. IQ and Load Exposure Data Set 7 “IQ and Lead” in Appendix B lists full IQ scores for a random sample of subjects with low lead levels in their blood and another random sample of subjects with high lead levels in their blood. The statistics are summarized below.
a. Use a 0.05 significance level to test the claim that the
b. Construct a confidence interval appropriate for tire hypothesis test in part (a).
c. Does exposure to lead appear to have an effect on IQ scores?
Low Blood Lead Level: n = 78,
High Blood Lead Level: n = 21,
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Elementary Statistics (13th Edition)
- Just answer the number 7 and 8 in 4 decimaalarrow_forward(a) For United States, provide data for the variables below over the years 1993 –2007:(i) Net migration rate (per 1,000 population)(ii) Total fertility rate (live births per woman)(iii)Unemployment, general level (Thousands)(iv) Wages(v) Life expectancy at birth for both sexes combined (years)Data can be obtained from the UN database http://data.un.org/Explorer.aspxUsing R-Studio, estimate a regression equation to determine the effect of unemployment,general level, wages and life expectancy at birth for both sexes on the net migration rate.(All codes and regression output should be provided).(i) Write down the regression equation. (ii) Interpret the coefficients and determine which of the individual coefficients in theregression model are statistically significant. In responding, construct and test anyappropriate hypothesis. (iii) Interpret the coefficient of determination.arrow_forwardThe article cited in Exercise 4 also investigated the effects of the factors on glucose consumption (in g/L). A single measurement is provided for each combination of factors (in the article, there was some replication). The results are presented in the following table. Glucose Consumption 68.0 -1 -1 -1 -1 -1 77.5 -1 -1 98.0 1. 1. -1 98.0 -1 -1 74.0 -1 77.0 -1 97.0 98.0 Compute estimates of the main effects and the interactions. a. Is it possible to compute an error sum of squares? Explain. Are any of the interactions among the larger effects? If so, which ones? d. Assume that it is known from past experience that the additive model holds. Add the sums of squares for the interactions, and use that result in place of an error sum of squares to test the hypotheses that the main effects are equal to 0. Ъ. C.arrow_forward
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