Questions 1. Consider the data sets below, determine if it is reasonable to assume that y is proportional to z. If it is, approximate the constant of proportionality. If it is not, describe why this assumption is not reasonable. I1 1.1 1.2 y11.2 1.44 1.4 1.69 1.96 2.25 | 2.56 | 2.89 1.3 1.5 1.6 1.7

According to an exit poll for an election, 55.1% of the sample size of 819 reported voting for a specific candidate. Is this enough evidence to predict who won? Test that the population proportion who voted for this candidate was 0.50 against the alternative that it differed from 0.50. Complete parts a through d below. OD. The parameter is the number of voters that voted for the candidate. Define the notation for the parameter. OA. p= the number of voters that did not vote for the candidate OB. p= the number of voters that voted for the candidate C. p=population proportion of voters that voted for the candidate D. p=sample proportion of votes for the candidate b. State the hypotheses and check the assumptions for a large-sample test. Choose the correct answer below. O A. Ho: p=0.50; H₂: p0.50 The assumptions for a large-sample test are met. c. Report the test statistic and P-value and interpret the latter. (Round to two decimal places as needed.) ... D F (1) More x

When water flows across farmland, some soil is washed away, resulting in erosion. An experiment was conducted to investigate the effect of the rate of water flow (liters per second) on the amount of soil (kilograms) washed away. The data are given in the following table:   Flow rate 0.31 0.85 1.26 2.47 3.75 Eroded soil 0.82 1.95 2.18 3.01 6.07           Let xx represent the flow rate variable and yy represent the variable for soil eroded. Then   \bar x = 1.73, s_x = 1.38, \bar y = 2.81, s_y = 1.99xˉ=1.73,sx​=1.38,yˉ​=2.81,sy​=1.99   Use this to complete the following calculation of the correlation coefficient for these data.   r = \frac{1}{n-1}\left[\left(\frac{x_1 - \bar x}{s_x}\right)\left(\frac{y_1 - \bar y}{s_y}\right) + \left(\frac{x_2 - \bar x}{s_x}\right)\left(\frac{y_2 - \bar y}{s_y}\right) + \cdots + \left(\frac{x_n - \bar x}{s_x}\right)\left(\frac{y_n - \bar y}{s_y}\right)\right]r=n−11​[(sx​x1​−xˉ​)(sy​y1​−yˉ​​)+(sx​x2​−xˉ​)(sy​y2​−yˉ​​)+⋯+(sx​xn​−xˉ​)(sy​yn​−yˉ​​)]…

The efficiency for a steel specimen immersed in a phosphating tank is the weight of the phosphate coating divided by the metal loss (both in mg/ft?). An article gave the accompanying data on tank temperature (x) and efficiency ratio (y). Temp. 173 175 176 177 177 178 179 180 Ratio 0.94 1.21 1.44 1.05 1.09 1.02 0.96 1.88 Temp. 183 183 183 183 183 184 184 185 Ratio 1.53 1.50 1.57 2.07 2.05 0.86 1.53 0.80 Temp. 185 185 185 187 187 188 189 191 Ratio 1.71 1.96 2.76 1.59 2.60 3.10 1.81 3.18 In USE SALT (a) Determine the equation of the estimated regression line. (Round all numerical values to four decimal places.) (b) Calculate a point estimate for true average efficiency ratio when tank temperature is 185. (Round your answer to four decimal places.) (c) Calculate the values of the residuals from the least squares line for the four observations for which temperature is 185. (Round your answers to two decimal places.) (185, 0.80) (185, 1.71) (185, 1.96) (185, 2.76) Why do they not all have…