The line of best fit through a set of data is ý = 38.241 – 1.827x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 20? y = Round to 1 decimal place.
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- The line of best fit through a set of data is y=−40.623+2.293xyAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 40?y = Round to 1 decimal place.One set of 20 pairs of scores, X and Y values, produces a correlation of r = 0.70. If SSY = 150, calculate the standard error of the estimate for the regression lineOn the second sheet is data which shows the rate of growth of a particular patch of bamboo vs daily high temperature.(a) Construct a scatterplot, including the equation of the line of best fit and value of R2.(b) What would the predicted growth rate be for a day with a temperature of 84◦?(c) Is there evidence, at α = 0.01, to support a claim that there is a linear relationship between temperature and growth rate? Please state clearly the null hypothesis, the alternative hypothesis, and what decision you make.
- A regression line for predicting test scores has an r.m.s. error of 8 points. When this result is used to predict test scores about 68% of the predictions will be right to within how many points?A regression line describes the relationship between the dependent and independent variables and can be used to estimate specific points for x or y, provided an individual is supplied with the values of all the other variables but one. True or falseYou spilled water on your calculations from (a) and can't remember what your estimated regression parameters are. But you do have two possible estimated errors for each of your initial four observations:
- ** had to resubmit this question because the first time the data was duplicated and reflected incorrectly. The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 2 3 4 5 5.5 6 Overall Grades 96 89 87 77 76 68 64 **Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes** Step 1 of 6 : Find the…If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that y and x are positively correlated.Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
- If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that y and x are positively correlated. True or false?One set of 10 pairs of scores, X and Y values produces a correlation of r= 0.40. If SSy = 200, find the standard of error of estimate for the regression line. You will need to calculate the SS residual first.#b. Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables (to 2 decimals).