In the packaging department of a large aircraft parts​ distributor, a fairly reliable estimate of packaging and processing costs can be determined by knowing the weight of an order.​ Thus, the weight is a cost driver that accounts for a sizable fraction of the packaging and processing costs at this company. Data for the past 10 orders are given as​ follows: a. Estimate the b0 and b1 ​coefficients, and determine the linear regression equation to fit these data. b. What is the correlation coefficient (R​)? c. If an order weighs 205 lb, how much should it cost to package and process​ it?                Packaging and Processing Cost​ ($), y Weight​ (Pounds), x 99 240 111 275 86 210 85 185 121 315 114 300 111 285 100 270 109 275 85 200

2.  Following data is amount of Assessed Value for an office building for a given floor area, number of office space, number of entrances, and the age of the offic building.   Use excel to ….   Obtain a Scatter plot of Floor Area as the independent and Assessed value as the dependent variable.  Note the linear regression Model  Predict the assessed value for 6000 sq ft.      FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4 2 8 1796 4720 3 2 12 1544 5940 4 2 2 2094 5720 4 2 34 1968 3660 3 2 38 1567 5000 4 2 31 1878 2990 2 1 19 949 2610 2 1 48 910 5650 4 2 42 1774 3570 2 1 4 1187 2930 3 2 15 1113 1280 2 1 31 671 4880 3 2 42 1678 1620 1 2 35 710 1820 2 1 17 678 4530 2 2 5 1585 2570 2 1 13 842 4690 2 2 45 1539 1280 1 1 45 433…

Please provide solution and logic for questions attached, thanks!

The following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers):   A.What would be the typical linear regression equation for the number of sales?    B.Make the sales forecast for period 15 of next year.    C. Make the sales forecast for period 17 of next year.      D. What is the standard error for the data?

15. Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $115 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions %3D 39 23 117 70 70 49 122 62 64 122 20 11 149 111 18 104 68 129 116 98 95 60 113 208 40 22 288 48 8. Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y = (Round to one decimal place as needed.) х. The best predicted gross for a movie with a $115 million budget is $ million. (Round to one decimal place as needed.)

The invasive diatom species Didymosphenia geminata has the potential to inflict substantial ecological and economic damage in rivers. An article described an investigation of colonization behavior. One aspect of particular interest was whether y = colony density was related to x = rock surface area. The article contained a scatterplot and summary of a regression analysis. Here is representative data. x 50 71 55 50 33 58 79 26 y 157 1934 53 27 7 10 40 12 x 69 44 37 70 20 45 49 y 274 43 176 18 48 190 30 (a) Fit the simple linear regression model to this data. (Round your numerical values to three decimal places.) y =       Predict colony density when surface area = 70 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony density       corresponding residual       Predict colony density when surface area = 71 and calculate the corresponding residual. (Round your answers to the nearest whole number.) colony…

46. Table 1.3 lists the ages and weights of nine girls. TABLE 1.3 Girls' Ages and Weights Age (months) Weight (pounds) 22 19 23 21 24 25 27 28 29 31 31 28 34 32 38 34 43 39 (a) Find the linear regression equation for the data. (b) Find the slope of the regression line. What does the slope represent? (c) Superimpose the graph of the linear regression equation on a scatter plot of the data. (d) Use the regression equation to predict the approximate weight of a 30-month-old girl..

Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume Total Cost (units) ($) 400 4,100 450 5,000 550 5,400 600 5,900 700 6,500 750 6,900 This data was used to develop an estimated regression equation, ŷ = 1,401.33 + 7.36x, relating production volume and cost for a particular manufacturing operation. Use a = 0.05 to test whether the production volume is significantly related to the total cost. (Use the F test.) State the null and alternative hypotheses. Hoi Bo = 0 Ha: Bo + 0 O Ho: B1 + 0 H: B1 = 0 Ho: B1 20 H: B, < 0 1 Ho: Bo + 0 Hạ: Bo = 0 Hoi B1 = 0 Set up the ANOVA table. (Round your p-value to three decimal places and all other values to two decimal places.) Source Sum Degrees of Freedom Mean F p-value of Variation of Squares Square Regression