logWage=B1+ B2 educ+ €, where 1. logWage means the log of yearly wage measured in dollars. 2. educ means years of education (schooling) The regression output is given below: . reg logwage educ Source | SS df MS Number of obs = 100 F(2, 97) = 97.20 Model 0.250000 1 .246632 Prob F = 0.0000 Residual 0.250000 98 .002537 R-squared = 0.5000 Adj R-squared = 0.4900 Total | 20000.00 99 200.00 Root MSE = 0.0503 logwage | Coef. Std. Err. t P>|t| [95% Conf. Interval] educ _cons 0.40000 5.00000 0.200000 2.00 0.050 0.0000000 0.800000 0.100000 10.00 0.000 4.8000000 5.200000 Question 5. The estimated confidence interval for ẞ2 at 95% confidence level is [0.00, 0.80]. Based on this estimate, which of the following statements is FALSE: (a) We can reject the hypothesis Ho: ẞ2 = 1 versus Ho: ẞ2 #1 at 5% significant level. (b) The p-value for the hypothesis testing of Ho: ß₂ = = 0.80 versus Hoẞ2 0.80 is 5%. (c) The estimate for 2 is the center of the interval. (d) We cannot reject the hypothesis Hoẞ2 = 0.1 versus Ho: ẞ2 0.1 at 5% significant level. (e) The true parameter 2 lies in the interval [0.00, 0.80] with probability 95%.

A popular television show recently released a video previewing the upcoming season on his website as fans of the show discovered the video the number of views of the preview video has grown each day during the last two weeks the number of days in the release of the video and the natural log of the number of video views as shown in the scatterplot. based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and numbers of views? an exponential model is appropriate because the Residual plot does not show a clear pattern A linear model is appropriate because of scatterplot shows a strong positive linear relationship A power model is appropriate because the scatterplot of days a natural log of use is strong and linear an exponential model is appropriate because the relationship between the days in the natural log of views in linear and the residual plot does not show a clear pattern

Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C

Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion).  Use the horizontal axis for the customer age to graph.  Find the linear regression line that models the data by each type of customer.  Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales.  What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y  / Change in x