Why does the sample size essential to consider in computing for skewness and kurtosis?
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A: Solution: Given information: x= 3.8333sx= 2.1370y=4.1833sy=1.5158r= - 0.9395
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A: Solution: Given information: n=6x= 3.5000sx= 2.5884y=4.2167sy=2.0469r= -0.9607
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Topic: Skewness and Kurtosis
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- (b) For the (x, y) data set of part (a), compute the equation of the sample least-squares line ŷ = a + bx. (Use 4 decimal places.) a b If the per capita spending was x = $39 one year, what do you predict for the spending the next year? (Use 2 decimal places.) $ per capita (c) Compute the sample correlation coefficient r and the coefficient of determination r2. (Use 4 decimal places.) r r2 Test ρ > 0 at the 1% level of significance. (Use 2 decimal places.) t critical t(a) The correlation coefficient: r = (b) The least squares line: ỹ = %3DA blood pressure measurement consists of two numbers: the systolic pressure, which is the maximum pressure taken when the heart is contracting, and the diastolic pressure, which is the minimum pressure taken at the beginning of the heartbeat. Blood pressures were measured, in millimeters, for a sample of 8 adults. The following table presents the results. Systolic Diastolic 124 84 106 84 102 77 113 77 118 66 117 87 130 74 115 70 The least-squares regression line y=b0+b1x=89.5234-0.1051x and Σ(x-x bar) squared =569.8750 are known for this data. Use the P-value method to test H0:β1=0 versus H1:β1<0. Can you conclude that systolic blood pressure is useful in predicting diastolic blood pressure? Use the α=0.10 level of significance and the TI-84 calculator. Compute the test statistic. Always round t-score values to three decimals places.
- A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.6667, sy = 2.2509, y= 3.6833, s, = 1.8809, and r= - 0.9511, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 1 4 4 6 6 y 5.0 6.3 4.2 3.4 1.4 1.8 (a) Choose the correct graph below. OA. B. OC. OD. Ay 74 Ay Ay 7- .. .. There appears to be a linear, negative relationship. (b) y=x+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. B. OC. D. Ay 0-A researcher wants to make an equation that will predict a person's support for domestic surveillance from a variety of demographic characteristics (e.g., age, income). What method will they use? A) Multiple regression B) Correlation C) Two-factor ANOVA D) One-sample t-testA data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y (b) Given that x =3.5000, s, = 2.2583, y = 4.4667, s, = 1.7682, and r= -0.9416, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 6 3 4 5.4 68 5.6 4.0 2.3 2.7 1 y (a) Choose the correct graph below. O A Oc. Q There appears to be V relationship (b) y=+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A OB. OC. OD.
- Performance IQ scores vs. brain size A study examinedbrain size (measured as pixels counted in a digitizedmagnetic resonance image [MRI] of a cross section ofthe brain) and IQ (4 Performance scales of the WeschlerIQ test) for college students. The scatterplot shows thePerformance IQ scores vs. the brain size. Comment onthe association between brain size and IQ.A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x = 3.6667, sx =2.4221, y = 3.8667, sy = 1.8435, andr= -0.9525, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). D O A. (a) Choose the correct graph below. Ay 6- X y 0 0 2 3 5 6 6 5.8 5.7 5.0 2.8 1.7 2.2 O G B. Ay 6- Q (...) C. 0- ● Q D. Ау 0- X 62nd pic sample photo:
- The table below shows the heights (inches) and weights (pounds) of 9 randomly selected children. Child Data Height (inches), x 36 56 58 59 61 63 65 69 73 Weight (pounds), y 69 89 96 74 110 90 123 110 128 (a) Construct a scatter diagram for the data, where the weight of the child is the response variable. (b) Determine the least-squares regression line for the data and graph the line on the scatter diagram from part (a). (use calculator) (show what did you do on the calculator) (c) Interpret the slope and the y–intercept in the context of the problem. (d) Predict the weight of a child that is 57 inches tall. Comparing with the observed value, what is the residual? Is the observed weight above or below average? (e) Determine the correlation coefficient, r. Is there a correlation? Discuss the strength of the correlation and why. (f) Are heights and weights of children linearly related? Why or why not? Be sure to justify your answer by using the appropriate method. (g)…A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x=3.8333, sx=2.4014, y=3.6500, sy=1.7942, and r=−0.9539, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a).Answer P1 please! Both parts of the question!
