1. If the coefficient of correlation (r) between two varlables is zero, how might a scatter diagram of these varlable appear?
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A: Univariate analysis is the simplest form of analyzing a data.
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- In a regression problem with 2 input variables, we construct a classification tree with 4 terminal nodes. This means(multiple choices) There was either four splits in only one of the input variables or one split in each of the input variable. There was a split in one of the input variables and no splits in the other. There was a split in each input variable. There was either a split in each input variable or three splits in only one of the input variables. There were 2 splits in each of the input variables.A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…I need help with this assaigment
- Can higher-order interactions be dropped to error in the analysis of fractional factorial designs? Why or why not ?Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin, - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team===== "Brooklyn Nets" . Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 None of the above 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 MS t Number of obs F(1, 80) Prob > F R-squared O The Nets lost more games than they won in 2014 P>|t| 2.77 0.007 -2.42 0.018 Adj R-squared = Root…What measures of fit are typically used to assess binary dependent variableregression models?
- Let Factor A have three levels and Factor B have five levels. If the interaction between A and B is significant, what is the value of ? for the q-curve if we are performing Tukey’s multiple-comparison procedure to determine which treatment means are different?An "extraneous variable" is not a problem unless it with the independent variable O is identical systematically co-varies is not correlated Wait! An "extraneous variable" is by definition never a problem, that's what "extraneous" means.1) For each of the following pairs of variables, is there likely to be a positive association, a negative association or no association? Briefly explain your reasoning. (a) Amount of alcohol consumed and performance on a test of coordination. (CHOOSE ONE) i) There is likely to be a positive association. As alcohol consumption increases, performance on a test of coordination will tend to increase. ii) There is likely to be a negative association. As alcohol consumption increases, performance on a test of coordination will tend to decrease. iii) No association would be expected between amount of alcohol consumed and performance on a test of coordination. (b) Height and grade point average for university students. i) There is likely to be a positive association. As height increases, grade point average for university students will tend to increase.There is likely to be a negative association. As height increases, grade point average for university students will tend to decrease.…