Q No. 1: The average amount of precipitation in Dallas, Texas, during the month of April is 3.5 inches (The World Almanac, 2000). Assume that a normal distribution applies and that the standard deviation is .8 inches. a) What percentage of the time does the amount of rainfall in April exceed 5 inches? b) What percentage of the time is the amount of rainfall in April less than 3 inches? c) What percentage of the time does the amount of rainfall in April between 2 to 4 inches? d) Amonth is classified as extremely wet if the amount of rainfall is in the upper 10% for that month. How much precipitation must fall in April for it to be classified as extremely wet? Q No. 2: Consider the data set in Table representing the ages (in years) and maintenance costs (in thousands of dollars per year) for five similar printing presses. Age : 5 9 8 Maintenance Cost: 13 23 UI 22 a) Find the correlation between age and maintenance cost. What do you learn from it? b) Find the least squares regression equation that predicts maintenance cost from the age of the machine. c) Interpret the regression equation which is obtained in (ii) d) Estimate the maintenance cost for the machine aging 7 years. Q No. 3 Robin Zill and Stewart Griffiths own a small company that manufactures portable massage tables in Hillsborough, North Carolina. Since they started the company, the number of tables they have sold is represented by this time series: Year 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Tables sold 42 50 61 75 92 111 120 127 140 138 (a) Find the linear equation that describes the trend in the number of tables sold by Robin and Stewart. (b) Estimate their sales of tables in 1998.Q No. 4: Sylvia Jensen, cost analyst for a major appliance firm, has compiled price data for four of the com- pany's products. The figures (given in unit prices) for 1993 through 1996 are shown in the table. Products 1993 1994 1995 1996 Dishwasher $219 $241 $272 $306 Washing machine 362 385 397 413 Dryer 229 241 261 275 Refrigerator 562 580 598 625 Using 1993 as the base period, express the prices in 1994,1995, and 1996 in terms of an unweighted aggregates index