Pro ta Fit Reply Advanced From HE Wat Oroup Text to a Home Des Console Cute Duplica Widation Unge ube Ir from the baba Test Query Xf KS2 U 1 ID kry wa Mipais Age Prome Service medel w Do not manipulate set on this page cocyto another pago to make changes The other 10 Ws 51 31 85 30 . 9 M M 4 14 32 10 41 36 36 0 0 1 0 4115 10 100 1 5 16 16 17 100 90 10 100 M M 1 1 1 1 + D 5. 15 16 SS 47 45 27 33 4 4.1 O 1 1 2 21.3 145 4 614 5 482 72 1 43 23.8 755 11 1 11 231 12 8 401 114 > F The came wheel IDe umple story Way toda Appen Performance Appring (map) Service Yeme - My predmete Grado de Degree (ISBAT-M Gender Male Complary dedy 06 1 A 1.000 1. 12 48 10 10 1 . 1 1 F 1 1 A A ! 100 99 19 22 1 YE 0 48 67 40 23 67 23 35 SY 40 20 13 40 17 11 33 31 12 30 4 47 M F C 13 v 32 44 0 M LITE 16 13 69 31 174 15 5.6 . 1 M A COM 0 36 VSE 13 44 49 48 10 10 95 65 M 0 15 35 IL DE 48 41 1 1 4 M CE 10 41 31 33 78 30 95 11 A A 1 2 08 + 14 61 WS 93 1 44 14 43 IN 12 49 8 10 . M M + D A 36 I . 1 M 8 40 N 13 14 15 LE 38 24 11 36 48 35 7 1 1 1 es 11 35 1 11 11 43 345 TE 1 61 61 41 6 0 16 611 44 96 71 3 414 PE 43 FI 41 + 31 19 With Wit J53 F G H L N o A D K Weck 1Descriptive Statisties, including Probability 2 While the lectures will examine our equal pay question from the comparatio viewpoint, our wookly assignments will focus on 3 camining the issue using the salary measure 4 The purpose of this assignment is twofold: 6.1. Demonstrate mustary with Excel tools. 7 2 Develop descriptive statistics to be examine the question 3. Interpect descriptive outcomes 19 The fint issue in examining salay due to determine if we los company - see paying males and females equally for doing equal work in to develop some 11 descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not 0 11 14 16 15 Descriptive Statisties: Develop basic descriptive statistics for Salary The first step in analyzing data sets is to find some summary descriptive statistics for key variables. Suggestion: Copy the gender and salary columns from the Dua tab to columns Tond Ut the night The use Da Son (by genderl) to get the male and female salary vale grouped together 12 Place Excel outcome in Cel K19 9 Use the Descriptive Statisties function in the Data Analysis tab to develop the descriptive statistics mmary for the overall group's evenly Place 19 in output range) Highlight the momple standard deviation, and mange 21 24 20 Using F (or formula) functions find the following (be sure to show the formula and not just the value in each cell) ked for salary statistics for each peder Male Female Mo Sumple Standard Deviation Rangs 30 302 Develop a sumber mary for the overall, male and female SALARY For full credit were de forma in each call rather than simply the more Ovani Male Female Mex 3rd Q Midpoin Tul 1 Locatie Mercom Maled Female midpoints to the ovell Salary data For follow the follrather than in the same Uning the way and the M Fmid found Wow would implementi be in the oven meg! Le PERCENTILANK EXC I STANDARDCE Probability Malone mit the Syd Follow for the dhe me Salary and the Moondise. Med The Play Thermal TUSI NORMES DEST Cude What do dichi ONE Weeks Week Weck Flash Fill Drououngou Subrot D L Connectant Car + AZ ? Properties Read From From New Database Refresh + Son Peter Text to Romove Data Consolidate HTML Wat if Teut Query Edit Links AB Advanced Columns Duplicates Validation R29 fo E 0 1 Week 2: Mentifying Significant Differences - part 1 2 To Ensure full credit for each question, you need to show how you got your results. This involves either showing where the data you used is located 4 or showing the excel formula in each cell Be sure to copy the appropriate data columns from the data tab to the right for your use this week 5 6 As with our examination of comparatio in the lecture, the first question we have about salury between the genders involves equality are they the same or different? 7 What we do, depends upon our findings B 3 1 Une Cell K10 for the Excel test outcome location. 19 11 As with the comparatio lecture example, we want to examine salary variation within the groups are they equal? What is the data input ranged used for this question: 0.856 through 1.247 b Which is needed for this question: a one or two-tail hypothesis statement and test? Answer: One Tail Why: So it shows they are not equal 12 13 14 15 16 17 10 e Step 1 Ho: Hae: Male companio variance Female comparatio variance Step 2: Significance (Alpha Step 3: Test Statistic and test Why this text? Step 4: Decision rule Step 5: Conduct the best place test function in cell klo 24 25 26 27 Step 6: Conclusion and Interpretation What is the p-value: What is your decision: REJO NOT reject the null? Why? What is your conclusion about the variance in the population for male and female salarie? Once we know about variance quality, we can move on to means: Are male and female avenge salaries equal? (Regardless of the outcome of the above F-test, assume equal variances for this test) What is the data input ranged used for this question: 31 2 Use Cell K35 for the Excel test outcome location. b Does this question need a one or two-tail hypothesis statement and test? Why Step 1 Ho: Ha: Step 2: Significance (Alpha) Step 3. Test Statistic and test: Why this test? Step 4 Deckion rules Wr 1 Week 2 Wook Weed + Data Select destination and press ENTER O choose Paste Trom HTU None All Advanced GOND Fil Columns ng Duplicates Validation Analysis From New Database TE Query x fic 129 B E F H L 49 Step 4 Decision rule: Step 5: Conduct the test place test function in cell K3S 44 45 44 47 45 Step 6: Conclusion and interpretation What is the p-value What is your decision: REJ or NOT reject the null? 49 Why? So What is your conclusion about the means in the population for male and female salarien? 62 53 58 50 Education is often a factor in pay differences Do employees with an advanced degree (degree - 1) have higher average salaries? Use Cell K60 for the Excel test outcome location. Note: assume equal variance for the salaries in each degree for this question 57 What is the data input ranged used for this question: b Does this question need a one or two-tail hypothesis statement and test? 60 Why 6. Sep 1: Ho 02 Ha: 03 Step 2: Significance (Alpha) 56 Step 3. Test Statistic and test: OS Why this test? Step 4: Decision rule: 67 Step 5: Conduct the test place test function in cell K60 60 09 Step 6 Conclusion and Interpretation 70 What is the peale 71 Is the value in the distribution til indicated by the 72 arrow in the Ha claim? What is your decision: RUJ or NOT reject the null? 74 Why? 75 at is your conclusion about the impact of education on avenge 78 salaries? 77 70 7 Considering both the comparatio infomation from the lectures and your salary information, what conclusions can you reach about equal pay for equal work? Your findings The related finding B3 Overall conclusion Why what atistical results support this conclusion? 05 bo 112 M Data Week 1 Week 2 Wook Week 4 NB. View he + WIN Wat MANOVA H AC LD >> CO CE Page Layout Formulas Rukw View 1. Az Te Q Ad Con DW Ut Anapas Det 0 D Owisy by die gewis Theksimiwa wa Wedd 0 U w the Sup1 Iles HE SA Sup Why Da Mahathi A M F the Catest . . 0 0 are the expected to the table A C Why NOTE Marth payale salariat 0 0 0 What do the wordt You My sharon panth 20 Week 2 Week Woch + & AZ 8 Data Review View Clear Real Sort Filter Advanced Grou Home Insert Draw Formulas Page Layout Connections Properties From From New Database Refresh 16 HTME Text Query A K11 fo Tect to Columns Flash Remove Consolidate Ft Duplicates Validation Asalysis N K Week 4 Identifying relationships. correlations and repression 3 To Ensure full credit for each question, you need to show how you get your results. This involves either showing where the date you used is located or showing the excel formals in each cell Be sure to copy the appropriate data columns from the data tab to the right for your use this weck 1 6 7 What is the correlation between and among the interval to level variables with lary? (Do not include compe-ruto in this question) Create the correlation table Use Cel Kos for the Esotest outcome location. What is the data input rungod wted for this question Crestes comicionable in cell KOR 5 10 11 13 Technically, we should perform a hypothesisting on each correlation to determine i significant or not. However, we can be ful to the process and save some time by finding the microelation that would result in a two tail rejection of the wall We can then compare each correlation to the value, and those exceeding is in either a positive or negative direction) can be considered Matistically significant What is the valve we would use to cut off the two mais? il What is the associated correlation value related to this value! 30 17 18 21 22 e. What will sure) signifiy cold towy? d. Are there any surprises -comelations you though would be significant und are nok, or the significant correlations you thought would be? & Why does or does not this information help answer our qual pay question 24 2 20 27 20 Perform a reason is wing clays the dependent variable and all of the variables used in QI. Add the two dummy variables-poder and education to your list of independent variables show the result, and interpret your findings by answering the following questions Sures: Add the dummy vriables vies to the right of the last data columns wiod for 01. 30 21 12 23 34 35 35 What is the male regression equation pedicting explaining all of our possible variables except compo? What is the data input ranged rod fequila Step 1: She propriate hypothes Use Call M34 for the Esceltest outcome location. Ho 30 30 Step 2 Siimat (Alpha Sap. Tot Sundst Why this test Stap 4: Decline Step 5. Conduct the inst-place test function in cell M34 Saepe Conclusion and Interpretario 4 44 What is your doc RE NOT reject the mall Why What is your conclusion about the factors influencing the population ay 41 40 00 If were all bypothes, we need to be significance of each of the vale coefficient Step 1: Sute the propriate coefficient hypothesis statement (Write a single pad we will it for cachbesparely) We 1 Wock 2 Woek Week 4 Select destination and press ENTIR O Choose Paste Refresh All Sort Edit Links Filter Advanced From HTML K11 From New Database Text Query fx Text to Columns Flash FA Conse Remove Data Duplicates Validation A B c D E F G H K M 49 50 51 52 53 55 56 87 58 50 If we rejected the null hypothesis, we need to test the significance of each of the variable coefficients. Step 1: State the appropriate coefficient hypothesis statements (Write a single pair, we will use it for each variable separately. Ho: Haz Step 2: Significance (Alpha); Step 3: Test Statistic and test: Why this test? Step 4. Decision rules Step 5: Conduct the test Note, in this case the test has been performed and is part of the Regression output above Step 6: Conclusion and interpretation Place the t and p-values in the following able Identify your decision on rejecting the null for each variable. If you reject the null, place the coefficient in the table Midpoint Age Perf. Rat Seniority Raise Gender Degree t-value: P-value: Rejection Decision Ir Null is rejected, what is the variable's coefficient value? 61 62 Using the intercept coefficient and only the significant variables, what is the equation? Salary d. 54 65 56 57 68 69 70 71 72 73 74 75 78 77 T8 79 30 81 Is gender a significant factor in salary? Regardless of statistical significance, who gets paid more with all other things being equal? How do we know? + 3 After considering the comparatio based results in the lectures and your say buted results, what else would you like to know before answering our oestion on equal pay? Why? 4 83 54 Between the lecture results and your results, what is your answer to the question of equal pay for equal work for tales and females? Why? Your findings The lecturer's related fieldings: Overall conclusion: What does rogression analysis show us about analyzing complex measures? 87 5 91 83 94 S6 00 97 Data Week 1 Week 2 Witch Week 4 Select destination and press ENTER or choose Paste Pro ta Fit Reply Advanced From HE Wat Oroup Text to a Home Des Console Cute Duplica Widation Unge ube Ir from the baba Test Query Xf KS2 U 1 ID kry wa Mipais Age Prome Service medel w Do not manipulate set on this page cocyto another pago to make changes The other 10 Ws 51 31 85 30 . 9 M M 4 14 32 10 41 36 36 0 0 1 0 4115 10 100 1 5 16 16 17 100 90 10 100 M M 1 1 1 1 + D 5. 15 16 SS 47 45 27 33 4 4.1 O 1 1 2 21.3 145 4 614 5 482 72 1 43 23.8 755 11 1 11 231 12 8 401 114 > F The came wheel IDe umple story Way toda Appen Performance Appring (map) Service Yeme - My predmete Grado de Degree (ISBAT-M Gender Male Complary dedy 06 1 A 1.000 1. 12 48 10 10 1 . 1 1 F 1 1 A A ! 100 99 19 22 1 YE 0 48 67 40 23 67 23 35 SY 40 20 13 40 17 11 33 31 12 30 4 47 M F C 13 v 32 44 0 M LITE 16 13 69 31 174 15 5.6 . 1 M A COM 0 36 VSE 13 44 49 48 10 10 95 65 M 0 15 35 IL DE 48 41 1 1 4 M CE 10 41 31 33 78 30 95 11 A A 1 2 08 + 14 61 WS 93 1 44 14 43 IN 12 49 8 10 . M M + D A 36 I . 1 M 8 40 N 13 14 15 LE 38 24 11 36 48 35 7 1 1 1 es 11 35 1 11 11 43 345 TE 1 61 61 41 6 0 16 611 44 96 71 3 414 PE 43 FI 41 + 31 19 With Wit J53 F G H L N o A D K Weck 1Descriptive Statisties, including Probability 2 While the lectures will examine our equal pay question from the comparatio viewpoint, our wookly assignments will focus on 3 camining the issue using the salary measure 4 The purpose of this assignment is twofold: 6.1. Demonstrate mustary with Excel tools. 7 2 Develop descriptive statistics to be examine the question 3. Interpect descriptive outcomes 19 The fint issue in examining salay due to determine if we los company - see paying males and females equally for doing equal work in to develop some 11 descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not 0 11 14 16 15 Descriptive Statisties: Develop basic descriptive statistics for Salary The first step in analyzing data sets is to find some summary descriptive statistics for key variables. Suggestion: Copy the gender and salary columns from the Dua tab to columns Tond Ut the night The use Da Son (by genderl) to get the male and female salary vale grouped together 12 Place Excel outcome in Cel K19 9 Use the Descriptive Statisties function in the Data Analysis tab to develop the descriptive statistics mmary for the overall group's evenly Place 19 in output range) Highlight the momple standard deviation, and mange 21 24 20 Using F (or formula) functions find the following (be sure to show the formula and not just the value in each cell) ked for salary statistics for each peder Male Female Mo Sumple Standard Deviation Rangs 30 302 Develop a sumber mary for the overall, male and female SALARY For full credit were de forma in each call rather than simply the more Ovani Male Female Mex 3rd Q Midpoin Tul 1 Locatie Mercom Maled Female midpoints to the ovell Salary data For follow the follrather than in the same Uning the way and the M Fmid found Wow would implementi be in the oven meg! Le PERCENTILANK EXC I STANDARDCE Probability Malone mit the Syd Follow for the dhe me Salary and the Moondise. Med The Play Thermal TUSI NORMES DEST Cude What do dichi ONE Weeks Week Weck Flash Fill Drououngou Subrot D L Connectant Car + AZ ? Properties Read From From New Database Refresh + Son Peter Text to Romove Data Consolidate HTML Wat if Teut Query Edit Links AB Advanced Columns Duplicates Validation R29 fo E 0 1 Week 2: Mentifying Significant Differences - part 1 2 To Ensure full credit for each question, you need to show how you got your results. This involves either showing where the data you used is located 4 or showing the excel formula in each cell Be sure to copy the appropriate data columns from the data tab to the right for your use this week 5 6 As with our examination of comparatio in the lecture, the first question we have about salury between the genders involves equality are they the same or different? 7 What we do, depends upon our findings B 3 1 Une Cell K10 for the Excel test outcome location. 19 11 As with the comparatio lecture example, we want to examine salary variation within the groups are they equal? What is the data input ranged used for this question: 0.856 through 1.247 b Which is needed for this question: a one or two-tail hypothesis statement and test? Answer: One Tail Why: So it shows they are not equal 12 13 14 15 16 17 10 e Step 1 Ho: Hae: Male companio variance Female comparatio variance Step 2: Significance (Alpha Step 3: Test Statistic and test Why this text? Step 4: Decision rule Step 5: Conduct the best place test function in cell klo 24 25 26 27 Step 6: Conclusion and Interpretation What is the p-value: What is your decision: REJO NOT reject the null? Why? What is your conclusion about the variance in the population for male and female salarie? Once we know about variance quality, we can move on to means: Are male and female avenge salaries equal? (Regardless of the outcome of the above F-test, assume equal variances for this test) What is the data input ranged used for this question: 31 2 Use Cell K35 for the Excel test outcome location. b Does this question need a one or two-tail hypothesis statement and test? Why Step 1 Ho: Ha: Step 2: Significance (Alpha) Step 3. Test Statistic and test: Why this test? Step 4 Deckion rules Wr 1 Week 2 Wook Weed + Data Select destination and press ENTER O choose Paste Trom HTU None All Advanced GOND Fil Columns ng Duplicates Validation Analysis From New Database TE Query x fic 129 B E F H L 49 Step 4 Decision rule: Step 5: Conduct the test place test function in cell K3S 44 45 44 47 45 Step 6: Conclusion and interpretation What is the p-value What is your decision: REJ or NOT reject the null? 49 Why? So What is your conclusion about the means in the population for male and female salarien? 62 53 58 50 Education is often a factor in pay differences Do employees with an advanced degree (degree - 1) have higher average salaries? Use Cell K60 for the Excel test outcome location. Note: assume equal variance for the salaries in each degree for this question 57 What is the data input ranged used for this question: b Does this question need a one or two-tail hypothesis statement and test? 60 Why 6. Sep 1: Ho 02 Ha: 03 Step 2: Significance (Alpha) 56 Step 3. Test Statistic and test: OS Why this test? Step 4: Decision rule: 67 Step 5: Conduct the test place test function in cell K60 60 09 Step 6 Conclusion and Interpretation 70 What is the peale 71 Is the value in the distribution til indicated by the 72 arrow in the Ha claim? What is your decision: RUJ or NOT reject the null? 74 Why? 75 at is your conclusion about the impact of education on avenge 78 salaries? 77 70 7 Considering both the comparatio infomation from the lectures and your salary information, what conclusions can you reach about equal pay for equal work? Your findings The related finding B3 Overall conclusion Why what atistical results support this conclusion? 05 bo 112 M Data Week 1 Week 2 Wook Week 4 NB. View he + WIN Wat MANOVA H AC LD >> CO CE Page Layout Formulas Rukw View 1. Az Te Q Ad Con DW Ut Anapas Det 0 D Owisy by die gewis Theksimiwa wa Wedd 0 U w the Sup1 Iles HE SA Sup Why Da Mahathi A M F the Catest . . 0 0 are the expected to the table A C Why NOTE Marth payale salariat 0 0 0 What do the wordt You My sharon panth 20 Week 2 Week Woch + & AZ 8 Data Review View Clear Real Sort Filter Advanced Grou Home Insert Draw Formulas Page Layout Connections Properties From From New Database Refresh 16 HTME Text Query A K11 fo Tect to Columns Flash Remove Consolidate Ft Duplicates Validation Asalysis N K Week 4 Identifying relationships. correlations and repression 3 To Ensure full credit for each question, you need to show how you get your results. This involves either showing where the date you used is located or showing the excel formals in each cell Be sure to copy the appropriate data columns from the data tab to the right for your use this weck 1 6 7 What is the correlation between and among the interval to level variables with lary? (Do not include compe-ruto in this question) Create the correlation table Use Cel Kos for the Esotest outcome location. What is the data input rungod wted for this question Crestes comicionable in cell KOR 5 10 11 13 Technically, we should perform a hypothesisting on each correlation to determine i significant or not. However, we can be ful to the process and save some time by finding the microelation that would result in a two tail rejection of the wall We can then compare each correlation to the value, and those exceeding is in either a positive or negative direction) can be considered Matistically significant What is the valve we would use to cut off the two mais? il What is the associated correlation value related to this value! 30 17 18 21 22 e. What will sure) signifiy cold towy? d. Are there any surprises -comelations you though would be significant und are nok, or the significant correlations you thought would be? & Why does or does not this information help answer our qual pay question 24 2 20 27 20 Perform a reason is wing clays the dependent variable and all of the variables used in QI. Add the two dummy variables-poder and education to your list of independent variables show the result, and interpret your findings by answering the following questions Sures: Add the dummy vriables vies to the right of the last data columns wiod for 01. 30 21 12 23 34 35 35 What is the male regression equation pedicting explaining all of our possible variables except compo? What is the data input ranged rod fequila Step 1: She propriate hypothes Use Call M34 for the Esceltest outcome location. Ho 30 30 Step 2 Siimat (Alpha Sap. Tot Sundst Why this test Stap 4: Decline Step 5. Conduct the inst-place test function in cell M34 Saepe Conclusion and Interpretario 4 44 What is your doc RE NOT reject the mall Why What is your conclusion about the factors influencing the population ay 41 40 00 If were all bypothes, we need to be significance of each of the vale coefficient Step 1: Sute the propriate coefficient hypothesis statement (Write a single pad we will it for cachbesparely) We 1 Wock 2 Woek Week 4 Select destination and press ENTIR O Choose Paste Refresh All Sort Edit Links Filter Advanced From HTML K11 From New Database Text Query fx Text to Columns Flash FA Conse Remove Data Duplicates Validation A B c D E F G H K M 49 50 51 52 53 55 56 87 58 50 If we rejected the null hypothesis, we need to test the significance of each of the variable coefficients. Step 1: State the appropriate coefficient hypothesis statements (Write a single pair, we will use it for each variable separately. Ho: Haz Step 2: Significance (Alpha); Step 3: Test Statistic and test: Why this test? Step 4. Decision rules Step 5: Conduct the test Note, in this case the test has been performed and is part of the Regression output above Step 6: Conclusion and interpretation Place the t and p-values in the following able Identify your decision on rejecting the null for each variable. If you reject the null, place the coefficient in the table Midpoint Age Perf. Rat Seniority Raise Gender Degree t-value: P-value: Rejection Decision Ir Null is rejected, what is the variable's coefficient value? 61 62 Using the intercept coefficient and only the significant variables, what is the equation? Salary d. 54 65 56 57 68 69 70 71 72 73 74 75 78 77 T8 79 30 81 Is gender a significant factor in salary? Regardless of statistical significance, who gets paid more with all other things being equal? How do we know? + 3 After considering the comparatio based results in the lectures and your say buted results, what else would you like to know before answering our oestion on equal pay? Why? 4 83 54 Between the lecture results and your results, what is your answer to the question of equal pay for equal work for tales and females? Why? Your findings The lecturer's related fieldings: Overall conclusion: What does rogression analysis show us about analyzing complex measures? 87 5 91 83 94 S6 00 97 Data Week 1 Week 2 Witch Week 4 Select destination and press ENTER or choose Paste