Year 1945 1946 1947 1948 1949 Storm number 1 2 3 3 4 5 4 5 6 7 8 6 7 8 9 10 11 9 1 2 3 4 5 6 7 9 1 2 3 4 5 6 7 8 1 2 3 4 5 199 6 7 1 2 Kainall depth (in) 0.38 0.47 0.39 0.76 0.56 0.35 0.43 0.4 0.36 0.62 0.55 0.88 0.47 0.36 1.15 0.75 1.53 0.51 0.88 2.04 0.76 0.97 0.71 1.07 0.94 1.2 1.33 0.65 0.47 0.84 0.68 0.63 0.47 0.52 0.49 Year 1950 1951 1952 1953 Storm number 1 2 3 2.5 2.04 4 5 1.53 1.33 1.3 1.27 1.02 0.97 0.85 0.76 0.52 1 2 3 4 5 6 1 2 tank (1-11 yrs) Rain-Fall Depth 1 2 3 4 5 7812345678 Rainfall depth (in) 0.55 0.63 0.69 1.27 1.1 0.88 0.97 0.59 0.46 0.5 0.55 0.47 1.2 0.93 0.7 0.57 0.46 0.48 1.3 0.4 0.45 0.53 2.5 1.03 0.75 0.7 1 Year 1954 1955 0.231 0.308 0.385 Storm number 1 0.462 0.538 0.615 0.692 0.769 0.846 2 3 4 HD68LAWN. 2 3 4 5 7 9 10 11 Kainfall depth (in) 0.42 0.7 0.85 0.6 0.7 0.95 1.02 0.5 0.65 0.55 0.45 0.54 0.6 Probability Return Period 0.077 0.154 0.8 0.95 13 7 4 3 3 2 2 2 1 1 1 Intensity 5 543 4 3 3 M M ~ ~ ~ ~A 3 2 2 2 2 1

In a test of the effectiveness of garlic for lowering cholesterol, 50 subjects were treated with garlic in a processed tablet form. Cholesterol levels were measured before and after the treatment. The changes (before - after) in their levels of LDL cholesterol (in mg/dL) have a mean of 3.2 and a standard deviation of 17.5. Construct a 95% confidence interval estimate of the mean net change in LDL cholesterol after the garlic treatment. What does the confidence interval suggest about the effectiveness of garlic in reducing LDL cholesterol? Click here to view at distribution table. Click here to view page 1 of the standard normal distribution table. Click here to view page 2 of the standard normal distribution table. C What is the confidence interval estimate of the population mean µ? mg/dL <μ< mg/dL (Round to two decimal places as needed.) What does the confidence interval suggest about the effectiveness of the treatment? O A. The confidence interval limits do not contain 0, suggesting…

1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the correlation coefficient is R and not R2) Principals x Teachers y 77.8 43.7 78.4 43.8 80.8 45.0 80.5 45.6 R=0.997497 81.5 45.9 2. Does the R value represent a positive, negative or no correlation between the salaries of the teachers and principals? As teacher salaries increase, what happens to 84.8 48.2 87.7 49.3 prinicipal salaries? 91.6 51.3 93.6 52.9 3. Write the equation of the regression line for the data below. The equation is y= 95.7 54.4 95.7 54.2 4. Use the regression equation that you found in exercise #3 to predict the average annual salary of public school classroom teachers when the average annual salary of public school principals is $139,723. Show your work in the cells to the right. (Be careful when entering the x-value in the equation. The table shows numbers that have been adjusted in terms of the thousands. Example: if the salary…

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3. MZMJK = K MZMJL %3D 27° MLJLK =. m/KML = m/MNL =. M

First Die 4 6. 1 3 4 6. 7 3 4 5. 6. 7. 8. 4 5. 6. 7 8. 9. 4 6. 7. 8. 9. 10 5 6. 8 6. 10 11 8. 9. 10 11 12 419 t in 47 Second Die

Two varieties of corn are grown in 4 different locations. Each location provides a value in pounds for each variety.The table below lists the results. Find the standard error for the difference in the production of the two corn varieties to two decimal places.   Variety 1 Variety 2 difference location 1 32.1 34.5 -2.4 location 2 30.6 32.6 -2.0 location 3 33.7 34.6 -0.9 location 4 29.7 31.6 -1.3 mean value 31.53 33.18 -1.65 standard deviation 1.76 1.72 0.68     1.23     0.75     0.34     0.98