Match each assumption on the left with the corresponding plot used to check it. Normally Distributed Residuals Linear Relationship between X and Y variables Constant variability of residuals Mean of the residuals is zero Q-Q Plot Studentized Residual Plot Profile Plot of Means Histogram Boxplot

A correlation near 0 indicates:   Group of answer choices   There is no relationship between variables There is a perfect linear relationship between variables There could be no relationship between variables or there could be a relationship that is no linear There are outliers in the data set

The weights of bags of baby carrots are normally​ distributed, with a mean of 29 ounces and a standard deviation of 0.34 ounce. Bags in the upper​ 4.5% are too heavy and must be repackaged. What is the most a bag of baby carrots can weigh and not need to be​ repackaged? A bag of baby carrots can weigh at most______  ounces without needing to be repackaged. (Round to two decimal places as​ needed.)

LINEAR CORRELATION PROJECT / Topic: Does per capita income affect birth rates    I need help with the trendline, the hypothesis, and conclusion, any confounding variables there might be and the r- value, and compare the r-value to the appropriate cutoff value, with correct interpretation.  (remember for a sample size of 20, the absolute value of r should be greater than 0.45) The regression equation is:    y=21.129−0.108xwhere y: average birth rate and x: per capita incomey and  x  is negatively related i.e with increase in x , y decreses and vice versa ((* for a sample size of 20, the absolute value of r should be greater than 0.45))     Country  Per Capita Income  Average Birth Rate Afghanistan  $                          530 37.9 Austria  $                    51,460 9.5 Cambodia  $                      1,530 23 Canada  $                    46,370 10.3 Denmark  $                    63,950 10.5 Ecuador  $                      6,090 17.9 Ethiopia  $…

Average Age and Length of Service The data show the average ages and lengths of service in months. Age 25 25.5 26.5 26.6 26.9 Time 66.2 71.2 72.6 88.1 82.7     The correlation coefficient for the data is  =r0.817  and  =α0.05 . Should regression analysis be done?     The regression analysis should not be done.     The regression analysis should be done.     Find the equation of the regression line. Round the coefficients to at least three decimal places.   =y′+abx     =a     =b     If a service person is  26.0  years old, predict the time that the person will serve. Round the answer to at least one decimal place.   Theservicepersonwillservemonths.