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- A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a bestfitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters.A scatterplot of the data along with the best fitting line is presented below. a. The correlation between the two variables is r = .89. Calculate and interpret the value of r2.b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30.c. How many books should the store order for a class of 50 students? Would you trust this prediction?please do c) find estimator by method of momentsDetermine the equation of a straight line that fits to the data points (1, 4), (2, 6), (3, 9), (4, 11), (5, 14), (6, 16). Round-off your answer to 2 decimal places. need asap
- Suppose an oceanographer monitors the daily salinity of a particular ocean in relation to the temperature of the water. The oceanographer plots the data with temperature, in degrees Celsius (°C), along the horizontal axis and salinity, in parts per thousand (ppt), along the vertical axis. Select the true statement about the data point identified by the arrow. An ocean temperature of 21 °C causes the salinity to be 29 ppt. The predicted salinity is 29 ppt when the ocean temperature for the day is 21 °C. An ocean temperature of 29 °C corresponds to a salinity level of 21 ppt. The observed salinity is 29 ppt when the ocean temperature for the day is 21 °C. There is no relationship between the temperature of the ocean on a given day and salinity.In order to find MSR and MSE, I need to find the p value. How do I do this?calculate p-value using t -table.
- Humaidi wants to verify the measurement of y-intercept estimate value that hemeasured based on 50 sample of trees so that the value can be apply to explainthe y-intercept for the population of 500 trees. He wrote the hypothesis as follows: H o : β 1 = 0H A : β 1 > 0 However, his lecturer says that his hypothesis statement is wrong. a)Why is that statement wrong? b)What should Humaidi write to make the hypothesis become right?Accountants at the Tucson firm, Larry Youdelman,CPAs, believed that several traveling executives were submittingunusually high travel vouchers when they returned from businesstrips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regres-sion equation relating expected travel cost to number of days on the road ( x1 ) and distance traveled ( x2 ) in miles:yn = +90.00 + +48.50x1 + +.40x2The coefficient of correlation computed was .68.a) If Donna Battista returns from a 300-mile trip that took herout of town for 5 days, what is the expected amount she shouldclaim as expenses?b) Battista submitted a reimbursement request for $685. Whatshould the accountant do?c) Should any other variables be included? Which ones? Why?A researcher for a tire company has collected data about the stopping distance in feet for different tire designs. The data range from 59 to 74 with an average of 65. Would it be better to have the origin at 0 on the axis, or at some other value? Explain. Yes, because all of the data values are less than 100, so 0 should be included. Yes, because 0 should always be included on the axis for a data set. No, because all of the data values fall in a small range which does not include or get close to 0. No, 0 should only be included in the values are less than 10.