The following table shows different prices of a product at certain weeks. x (Weeks) y (Price($)) 4. 24.3 28.45 6. 29.8 29.85 8. 33.7 9. 35.85 10 36.4 11 35.45 (a) Based on the data shown above, compute the correlation coefficient accurate to three decimal places. T = (b) Find the proportion of the variation in Price that can be explained by the variation in the values of Weeks. Report your answer as a percentage accurate to one decimal place. (Example: If the answer is 0.1234, you would enter 12.3 without the percent symbol.)

DVD Player sales The table shows the number of DVD play-ers sold in a small electronics store in the years 2003-2013. What was the average rate of change of sales between 2003 and 2013? Whatwas the average rate of change of sales between 2003 and 2004? What was the average rate of change of sales between 2004 and 2005? Between which two successive years did DVD player sales increase most quickly?

What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?

Calculate trend values by the method of least square from the data given below and estimate the sales for 1983 : Year 1976 1977 1978 1979 1980 : Sales of Co. ('000,000) : 70 74 80 86 90

What is the lower bound and Upper bound

A negative correlation means that decreases in the X variable tend to be accompanied by decreases in the Y variable. T or F

The data in the tables below, comprises of the number of hours (X) studied and the exam grade (Y) obtained for 6 first year students registered at UWC. Calculate the slope (rounded off to four decimals). X 2 5 1 2 3 3 Y (%) 60 85 73 80 90 87   SSxy = 42.33 SSx = 9.33 SSy = 618.83  = 2.6667  = 79.1667 b = 4.53567

The correlation between hours of sleep and hours of study is r = 0.14. (a) Calculate r². (Round your answer to four decimal places.) ,2 = = (b) Choose a sentence that interprets value r². 1.96% of the variation in hours of sleep is not explained by hours of study. Variation in hours of study explains about 1.96% of the observed variation in hours of sleep. 1.96% of the variation in hours of sleep is not explained by the variation in hours of study. Hours of study explains about 1.96% of the observed variation in hours of sleep.

X 3.29 The quarterly revenues of a small medical supply company for the last several years (27 quarters) were plotted and seen to have a roughly linear trend component. The information below was computed for y₁. Y₂..... Y27 using one of the company's spreadsheet computer programs. t=1,2,..., 27 y, quarterly gross revenues ($10,000) Σ y = 7,146 3ty w 113,615 SS-120,640 a. Using the method of least squares, fit a linear trend model to the revenue data. b. Test for significance of the trend component assuming indepen- dent, normally distributed error terms. c. Forecast revenues for t= 28 and t = 29 using the model fit in part (a). d. Construct 95% prediction intervals for y28 and Y29- e. Construct 90% prediction intervals for y2a and Y20

The data in the accompanying table represent the rate of return of a certain company stock for 11​ months, compared with the rate of return of a certain index of 500 stocks. Both are in percent. Complete parts ​(a) through ​(d) below. Rate of Return Month Rates of return of the​index, x Rates of return of the company​ stock, y   ​Apr-18 4.234.23             3.283.28               ​May-18 3.353.35             5.095.09               ​Jun-18 negative 1.78−1.78             0.540.54               ​Jul-18 negative 3.20−3.20             2.882.88               ​Aug-18 1.291.29             2.692.69               ​Sept-18 3.583.58             7.417.41               ​Oct-18 1.481.48             negative 4.83−4.83               ​Nov-18 negative 4.40−4.40             negative 2.38−2.38               ​Dec-18 negative 0.86−0.86             2.372.37               ​Jan-19 negative 6.12−6.12…