QUESTION 2.2 We can conclude that this correlation is: Choose one - 2 points 0 perfect and positive 0 strong and positive 0 moderate and positive 0 weak and positive QUESTION 2.3 The model (equation) exactly as it is: y = A (HINT: please write it exactly as it appears in Excel) Enter an answer ' 2 points QUESTION 2.4 If we have nitrate levels of 2300, then the absorbence is predicted to be A If we have nitrate levels of 25, then the absorbence is predicted to be B If we have nitrate levels of 560, then the absorbence is predicted to be C (note: please round to 4 decimal spaces) Enter an answer . 15 pointsUse the College Graduates and Salaries data file (below) to answer each problem. We want to determine if there is a correlation between SAT scores and salaries of individuals who finished a college degree. For that purpose, we collected the salaries and SAT scores of 50 people. 0 Calculate the correlation coefficient of the data. Round to 4 decimal places. 0 What conclusion can you make about the correlation of this data? 0 What is the regression equation ofthis data? 0 Use the regression equation to predict what would be the salary given the following SAT scores. Round to 2 decimal places. 1.1100 2.978 3' 750 @ CollegeGraduatesandSalariesDataset.xlsx 10 KB QUESTION 3.1 The correlation coefficient of this data is A (note: please round to the thousands or 4 decimal spaces) Enter an answer - 5 points AutoSave O OFF ~ W E . 5 : CollegeGraduatesandSalariesDataset Home Insert Draw Page Layout Formulas Data Review View Tell me Share Comments & Cut Calibri (Body) v 12 AA 27 V DE Copy v Wrap Text v General Normal Bad AutoSum ~ As Paste Format BIUV MVA EE Merge & Center v $ ~ % " 09 300 Conditional Format Good Neutral Fill v Insert Delete Format Formatting as Table Clear v Sort & Find & Analyz Sensitivity Filter Select Data Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? Yes No E25 + X V fx G H M N P Q R W Salary SAT Score AA 31144 1029 47951 934 3217 944 29934 1005 41078 902 34571 986 50045 908 39076 897 3258 889 32291 854 38518 889 29783 956 39431 1048 15 36785 882 31511 1099 34652 1060 32257 999 26461 1021 31972 896 40661 909 40795 907 41895 1033 35948 1045 26818 1036 31189 1045 2878 1009 30922 1050 34836 917 3472 935 46087 898 w 28493 1015 47612 892 30793 865 26327 1107 36802 975 28172 1027 38555 947 44516 880 40729 388 Sheet1 + 100%QUESTION 3.2 We can conclude that this correlation is: Choose one - 2 points 0 strong negative 0 moderate negative 0 weak negative 0 perfect negative QUESTION 3.3 Enter the model (equation) exactly as it is Excel (do NOT round) y=A Enter an answer ' 2 points QUESTION 3.4 If the score is 1100, the prediction is A If the score is 978, the prediction is B If the score is 750, the prediction is C (Note: round to two decimal spaces) Enter an answer '15 points Use the Play Ball dataset (below) to answer these questions. As a sports businessperson, you want to determine whether the total numbers of innings pitched by a pitcher (IP) has any relationship to the number of home runs allowed by a pitcher (HR). This will help you negotiate several player contracts with their respective teams. To this end, you have gathered data from the MLB website 0 Calculate the correlation coefficient of the data' Round to 4 decimal places 0 What conclusion can you make about the correlation of this data? 0 What is the regression equation ofthis data? 0 Use the regression equation to predict what would be the HR given the following lP. Round to 2 decimal places. 1. 50 2. 63 3. 70 @ PlayBallDatasetxlsx 9 KB QUESTION 4.1 The correlation coefficient of this data is A 3. PlayBallDataset AutoSave O OFF ~ E . 5 : Share Comments Home Insert Draw Page Layout Formulas Data Review View Tell me Bad AutoSum ~ As Normal & Cut Calibri (Body) v 12 AA 27 V Wrap Text v General Fill v Sort & Find & Analyz Sensitivity [E Copy v Good Neutral Insert Delete Format Select Merge & Center v $ ~ % 9 Conditional Format Clear v Filter Data Paste Format BIUV Formatting as Table Yes No Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? E24 X V fx W Z AA H M P Q Name Box G w J W W VI N 64.2 66 57.2 65.1 55 72.2 60 $4.2 52.2 55.2 57.1 56.1 55.2 $5.1 14.2 57 56 58.2 58 45.1 60.1 66.1 45 56.2 65.1 55.1 54.2 56.2 59 55 37 54.9 52 39 49.1 59.2 Sheet1 + 100%QUESTION 4.2 We can conclude that this correlation is: Choose one - 2 points 0 strong and negative 0 perfect and negative 0 weak and negative 0 moderate and negative QUESTION 4.3 Enter the model (equation) exactly as it is Excel (do NOT round) y=A Enter an answer - 2 points QUESTION 4.4 If the IP is 50, the prediction is A If the IP is 63, the prediction is B If the IP is 70, the prediction is C (Note: Round to two decimal spaces) Enter an answer ~15 points QUESTION 5.1 Now that you have constructed three different correlation and regression models, which one do you think is the best? Why? Hint: calculate the coefficient of determination of each and use it to support your answer. Response . 10 points B U S- JJ Your response... 0 words ATTACH FILE(S) DRAG & DROP Max size 4.0 GBImage description: enlarged water drops and wave. The water is clear and the background is light blue. Use the Clean Water data files (below) to answer each problem. Problem 1 Keeping water supplies clean requires regular measurement of the levels of pollutants. Their measurements are indirect usually requiring forming a dye by a chemical reaction with the dissolved pollutant and then passing light through the solution to measure its "absorbance". This is done everyday. 0 Calculate the correlation coefficient of the data. Round to 4 decimal places. 0 What conclusion can you make about the correlation of this data? 0 What is the regression equation ofthis data? 0 Use the regression equation to predict what would be the absorbance of the following nitrate levels. Round to 4 decimal places. 'I. 2300 2. 25 3. 560 a CleanWaterDataSet.xlsx 9 KB QUESTION 2.1 The correlation coefficient of this data is A AutoSave O OFF ~ H E . 5 : 3CleanWaterDataSet Home Insert Draw Page Layout Formulas Data Review View ? Tell me Share Comments & Cut Calibri (Body) v 12 AA 27 V Wrap Text v General Normal Bad AutoSum ~ A CE Copy v Fill v Paste 00 0 Conditional Format Good Neutral Format Sort & Format IUV Merge & Center $ ~ % 9 Insert Delete Find & Clear Analyz Sensitivity Formatting as Table Filter Select Data Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? Yes No D28 X V fx D E G H K L M N P Q R W X AA Nitrates Absorbence 2 50 50 w 7.5 100 2.8 200 24 400 47 800 93 1200 138 1600 183 10 2000 230 2000 226 12 13 14 15 16 17 18 19 20 21 Sheet1 + 100%