In a research project, the researcher normally has a research question in mind and then develops a research methodology. The methodology includes such things as determining the type of data that will be needed to address the question, how the data will be collected, and how the data will be analyzed. Due to time constraints, you will take a different approach to developing a research question. You will be given data that has already been collected and asked to develop a possible research question from the data. For this discussion activity, open the StatCrunch file(below), Southwest Airlines Data. The variables are explained within the file description. DayOfWeek Carrier Origin Dest CRSDepTime DepTime DepDelayMinutes DepDel15DepTimeBlk TaxiOut WheelsOff WheelsOn TaxiIn CRSArrTime ArrTime ArrDelayMinutes ArrDel15 ArrTimeBlk CRSElapsedTime ActualElapsedTime AirTime Distance DistanceGroup 2 WN MDW ABQ 1005 1005 0 0 1000-1059 9 1014 1149 3 1215 1152 0 0 1200-1259 190 167 155 1121 5 2 WN MDW ABQ 2015 2042 27 1 2000-2059 6 2048 2224 7 2230 2231 1 0 2200-2259 195 169 156 1121 5 2 WN MDW ALB 1705 1725 20 1 1700-1759 8 1733 2007 3 2000 2010 10 0 2000-2059 115 105 94 717 3 2 WN MDW ALB 1230 1228 0 0 1200-1259 7 1235 1512 3 1520 1515 0 0 1500-1559 110 107 97 717 3 2 WN MDW AUS 2055 2107 12 0 2000-2059 8 2115 2328 4 2340 2332 0 0 2300-2359 165 145 133 972 4 2 WN MDW AUS 1215 1235 20 1 1200-1259 7 1242 1448 6 1500 1454 0 0 1500-1559 165 139 126 972 4 2 WN MDW BDL 1415 1430 15 1 1400-1459 11 1441 1728 8 1725 1736 11 0 1700-1759 130 126 107 777 4 2 WN MDW BDL 930 1000 30 1 0900-0959 10 1010 1254 4 1235 1258 23 1 1200-1259 125 118 104 777 4 2 WN MDW BDL 2105 2125 20 1 2100-2159 12 2137 15 4 10 19 9 0 0001-0559 125 114 98 777 4 2 WN MDW BHM 1015 1012 0 0 1000-1059 8 1020 1130 2 1200 1132 0 0 1200-1259 105 80 70 570 3 2 WN MDW BHM 2115 2205 50 1 2100-2159 8 2213 2328 3 2300 2331 31 1 2300-2359 105 86 75 570 3 2 WN MDW BNA 545 557 12 0 0001-0559 22 619 712 6 710 718 8 0 0700-0759 85 81 53 395 2 2 WN MDW BNA 1955 2054 59 1 1900-1959 6 2100 2154 5 2115 2159 44 1 2100-2159 80 65 54 395 2 2 WN MDW BNA 1700 1715 15 1 1700-1759 7 1722 1816 6 1825 1822 0 0 1800-1859 85 67 54 395 2 2 WN MDW BNA 1010 1010 0 0 1000-1059 7 1017 1111 6 1130 1117 0 0 1100-1159 80 67 54 395 2 2 WN MDW BNA 710 748 38 1 0700-0759 14 802 853 6 835 859 24 1 0800-0859 85 71 51 395 2 2 WN MDW BNA 1335 1334 0 0 1300-1359 6 1340 1435 5 1455 1440 0 0 1400-1459 80 66 55 395 2 2 WN MDW BNA 2125 2154 29 1 2100-2159 6 2200 2255 6 2245 2301 16 1 2200-2259 80 67 55 395 2 2 WN MDW BOS 1615 1638 23 1 1600-1659 6 1644 1936 9 1940 1945 5 0 1900-1959 145 127 112 861 4 2 WN MDW BOS 2010 2011 1 0 2000-2059 9 2020 2311 4 2325 2315 0 0 2300-2359 135 124 111 861 4 0 0700-0759 7 721 741 3 805 744 0 0 0800-0859 110 90 80 562 3 5 WN DAL ELP 1145 1143 0 0 1100-1159 8 1151 1210 8 1230 1218 0 0 1200-1259 105 95 79 562 3 5 WN DAL ELP 1805 1815 10 0 1800-1859 8 1823 1848 4 1850 1852 2 0 1800-1859 105 97 85 562 3 5 WN DAL ELP 1940 2012 32 1 1900-1959 16 2028 2053 3 2035 2056 21 1 2000-2059 115 104 85 562 3 5 WN DAL HOU 700 658 0 0 0700-0759 10 708 754 5 800 759 0 0 0800-0859 60 61 46 239 1 5 WN DAL HOU 730 731 1 0 0700-0759 7 738 821 4 835 825 0 0 0800-0859 65 54 43 239 1 5 5 5 5 5 5 WN 6 WN 4 WN 6 WN 6 WN 6 WN 5 DAL 900 DAL 930 DAL 1000 DAL 1030 DAL 1100 DAL 1200 HOU 854 HOU 925 HOU 953 HOU 1026 HOU 1055 HOU 1153 800 0 830 0 900 0 930 0 1000 0 1100 0 756 0 829 0 857 0 930 0 959 0 1058 0 0 0 0900-0959 0 0 0900-0959 0 0 1000-1059 0 0 1000-1059 0 0 1100-1159 0 0 1200-1259 0800-0859 60 58 0800-0859 60 56 0900-0959 60 56 0900-0959 60 56 1000-1059 60 56 1100-1159 60 55 8 44 8 44 6 44 5 45 7 43 8 42 804 239 837 239 903 239 935 239 1006 239 1106 239 848 1 921 1 947 1 1020 1 1049 1 1148 1 This discussion is a lead-in to the t-Test Course Project that you will be working on in the next module. You will be asked to do something similar to this activity for your project and also asked to collect and analyze the data. Look at the description of the variables in the file and the variables themselves. Then develop a \"research question\" that can be answered using a one- or two-sample t-test and confidence interval that might be interesting to explore using this data set. Some examples are: -Is the average delay time longer at Midway than at Dallas? -Is the average taxi time longer at Houston than at Dallas? Develop your own research question. Be creative! Try to find something that might be interesting to you. After you write your question, also indicate the techniques you would use to answer it. For this Discussion, you don't need to analyze the data. You only need to develop a research question. The first part of this project involves selecting an appropriate research question and data source. This means you need to select a research question that can be answered using a t-test and selecting a data file, website with appropriate data available, or developing a plan for collecting the data yourself. Normally, another option would be to conduct a survey. How should you proceed with selecting a topic? Follow this criteria before you pose your research question and data source. Look at the resources contained in the documents below. Review the sample projects. Give serious thought about your own interests. Most important... Be original! 1. The 1-sample t-test Required elements: one population, one quantitative variable, a specific value for hypothesis Example scenario: Population: All 2-bedroom apartments in Lumpkin County Variable: monthly rent Research question: Is the average rent for a 2 bedroom apartment in Lumpkin County more than $600 per month? Hypothesis and rationale: \"I predicted that the average monthly rent for a twobedroom apartment in Lumpkin County would be higher than $600. A college planning guide stated that students could probably share a 2-bedroom apartment off campus \"for about $600 a month.\" Based on casual observation, I believe that on average, this estimate is too low.\" 2. The matched pairs t-test Required elements: a) one quantitative variable and two populations in which individuals can be matched OR b) one population and two quantitative variable values for each individual For both (a) and (b) the hypothesis is about the computed difference between the two related values Example scenario for (a): Populations: All canned vegetables sold at Kroger; all canned vegetables sold at Wal-Mart Variable: price (*specifically, the difference in price charged for identical items at each store) Research question: On average, are canned vegetables cheaper at Wal-Mart than at Kroger? Hypothesis and rationale: \"We predicted that on average, Wal-Mart would charge less for the same canned vegetable item. This prediction is based on the general observation that things seem to cost less at Wal-Mart.\" Example scenario for (b): Population: All NGCSU students Variables: rating (1 - 10) of the taste of Coke; and rating (1-10) of the taste of Pepsi (*specifically, taste tests are conducted \"blind\" and the difference in ratings is computed for each participant) Research question: On average, do NGCSU students prefer Coke over Pepsi? Hypothesis and rationale: \" We predicted that on average NGCSU students would rate Coke better in taste than Pepsi. This prediction is based on the fact that in such close proximity to Atlanta, the Coca Cola capital, Coke is often the preferred soft drink.\" 3. The 2-sample t-test (independent samples) Required elements: two populations, one variable Example scenario: Populations: 1) All current NFC football players; 2) All current AFC football players Variable: age Research question: Is there a significant difference between the average age of NFC players and AFC players? (by \"significant\" we mean statistically significant) Hypothesis and rationale: \"We predicted that there might be a difference between the average age of NFC and AFC players. In recent years, the AFC has been perceived as the stronger conference; one could theorize that on average, they have older players who are wiser and more experienced; OR one could theorize that on average, they have younger players who are in better shape and have more stamina. The purpose of this study is to determine if any such age discrepancy exists.\" in study,people were observed for about 10 seconds in public places such as mall and restaurant to determine whether they smiled during the randomly chosen 10 second interval,the table shows the results for comparing males and females,complete parts : male females smile 3308 4315 no smile 3770 4203 find and compare the sample percentage of men who were smiling and women who are smiling: a)the percentage of men who were smiling in the sample was 46.74% ? b)the percentage of women who were smiling in the sample was 50.66% ? c)the percentage of people who were smiling was greater for Females d)determine the hypotheses for this test ,let p1 represent the population proportion for men who smile and let p2 represent for women who smile choose the correct answer... 1)H0:P1p2 6) H0:p1not equal p2 Ha:P1>P2 Ha:p1=p2 Ha:p1=p2 Correct answer: Ha:p1 not equal to p2 Find the test statistic z=-4.88 round to two decimal places Find p value = 0.000 to three decimal places What is the conclusion for this test?use significance level of 0.01 a)do not reject H0 there is not significant difference in rate for smiling for men and women b)reject H0 there is not significant difference in rate for men and women c)do not reject H0:there is significant in rate of smiling for men and women d)reject h0:there is significant difference in rate of smiling for men and women explain the size of the p value compared to diferernce in the sample percentage choose the correct answer... 1)the p value is small compared to the small relative difference in the sample percentage because a small difference leads to large absolute value of the test statistic and a small pvalue 2)the p value is large compared to the small relative difference inn the sample percentage because of the small sample size 3)the p value is large compared to the small relative difference in the sample percentage because a small difference leads to small absolute value of the test statistic and a large p value. 4)the p value is small compared to the small relative diferrence in the sample percentages because of the large sample size 1) In a research project, the researcher normally has a research question in mind and then develops a research methodology. The methodology includes such things as determining the type of data that will be needed to address the question, how the data will be collected, and how the data will be analyzed. Due to time constraints, you will take a different approach to developing a research question. You will be given data that has already been collected and asked to develop a possible research question from the data. For this discussion activity, open the StatCrunch file(below), Southwest Airlines Data. The variables are explained within the file description. DayOfWeek Carrier Origin Dest CRSDepTime DepTime DepDelayMinutes DepDel15DepTimeBlk TaxiOut WheelsOff WheelsOn TaxiIn CRSArrTime ArrTime ArrDelayMinutes ArrDel15 ArrTimeBlk CRSElapsedTime ActualElapsedTime AirTime Distance DistanceGroup 2 WN MDW ABQ 1005 1005 0 0 1000-1059 9 1014 1149 3 1215 1152 0 0 1200-1259 190 167 155 1121 5 2 WN MDW ABQ 2015 2042 27 1 2000-2059 6 2048 2224 7 2230 2231 1 0 2200-2259 195 169 156 1121 5 2 WN MDW ALB 1705 1725 20 1 1700-1759 8 1733 2007 3 2000 2010 10 0 2000-2059 115 105 94 717 3 2 WN MDW ALB 1230 1228 0 0 1200-1259 7 1235 1512 3 1520 1515 0 0 1500-1559 110 107 97 717 3 2 WN MDW AUS 2055 2107 12 0 2000-2059 8 2115 2328 4 2340 2332 0 0 2300-2359 165 145 133 972 4 2 WN MDW AUS 1215 1235 20 1 1200-1259 7 1242 1448 6 1500 1454 0 0 1500-1559 165 139 126 972 4 2 WN MDW BDL 1415 1430 15 1 1400-1459 11 1441 1728 8 1725 1736 11 0 1700-1759 130 126 107 777 4 2 WN MDW BDL 930 1000 30 1 0900-0959 10 1010 1254 4 1235 1258 23 1 1200-1259 125 118 104 777 4 2 WN MDW BDL 2105 2125 20 1 2100-2159 12 2137 15 4 10 19 9 0 0001-0559 125 114 98 777 4 2 WN MDW BHM 1015 1012 0 0 1000-1059 8 1020 1130 2 1200 1132 0 0 1200-1259 105 80 70 570 3 2 WN MDW BHM 2115 2205 50 1 2100-2159 8 2213 2328 3 2300 2331 31 1 2300-2359 105 86 75 570 3 2 WN MDW BNA 545 557 12 0 0001-0559 22 619 712 6 710 718 8 0 0700-0759 85 81 53 395 2 2 WN MDW BNA 1955 2054 59 1 1900-1959 6 2100 2154 5 2115 2159 44 1 2100-2159 80 65 54 395 2 2 WN MDW BNA 1700 1715 15 1 1700-1759 7 1722 1816 6 1825 1822 0 0 1800-1859 85 67 54 395 2 2 WN MDW BNA 1010 1010 0 0 1000-1059 7 1017 1111 6 1130 1117 0 0 1100-1159 80 67 54 395 2 2 WN MDW BNA 710 748 38 1 0700-0759 14 802 853 6 835 859 24 1 0800-0859 85 71 51 395 2 2 WN MDW BNA 1335 1334 0 0 1300-1359 6 1340 1435 5 1455 1440 0 0 1400-1459 80 66 55 395 2 2 WN MDW BNA 2125 2154 29 1 2100-2159 6 2200 2255 6 2245 2301 16 1 2200-2259 80 67 55 395 2 2 WN MDW BOS 1615 1638 23 1 1600-1659 6 1644 1936 9 1940 1945 5 0 1900-1959 145 127 112 861 4 2 WN MDW BOS 2010 2011 1 0 2000-2059 9 2020 2311 4 2325 2315 0 0 2300-2359 135 124 111 861 4 0 0700-0759 7 721 741 3 805 744 0 0 0800-0859 110 90 80 562 3 5 WN DAL ELP 1145 1143 0 0 1100-1159 8 1151 1210 8 1230 1218 0 0 1200-1259 105 95 79 562 3 5 WN DAL ELP 1805 1815 10 0 1800-1859 8 1823 1848 4 1850 1852 2 0 1800-1859 105 97 85 562 3 5 WN DAL ELP 1940 2012 32 1 1900-1959 16 2028 2053 3 2035 2056 21 1 2000-2059 115 104 85 562 3 5 WN DAL HOU 700 658 0 0 0700-0759 10 708 754 5 800 759 0 0 0800-0859 60 61 46 239 1 5 WN DAL HOU 730 731 1 0 0700-0759 7 738 821 4 835 825 0 0 0800-0859 65 54 43 239 1 5 5 5 5 5 5 WN 6 WN 4 WN 6 WN 6 WN 6 WN 5 DAL 900 DAL 930 DAL 1000 DAL 1030 DAL 1100 DAL 1200 HOU 854 HOU 925 HOU 953 HOU 1026 HOU 1055 HOU 1153 800 0 830 0 900 0 930 0 1000 0 1100 0 756 0 829 0 857 0 930 0 959 0 1058 0 0 0 0900-0959 0 0 0900-0959 0 0 1000-1059 0 0 1000-1059 0 0 1100-1159 0 0 1200-1259 0800-0859 60 58 0800-0859 60 56 0900-0959 60 56 0900-0959 60 56 1000-1059 60 56 1100-1159 60 55 8 44 8 44 6 44 5 45 7 43 8 42 804 239 837 239 903 239 935 239 1006 239 1106 239 848 1 921 1 947 1 1020 1 1049 1 1148 1 This discussion is a lead-in to the t-Test Course Project that you will be working on in the next module. You will be asked to do something similar to this activity for your project and also asked to collect and analyze the data. Look at the description of the variables in the file and the variables themselves. Then develop a \"research question\" that can be answered using a one- or two-sample t-test and confidence interval that might be interesting to explore using this data set. Some examples are: -Is the average delay time longer at Midway than at Dallas? -Is the average taxi time longer at Houston than at Dallas? Develop your own research question. Be creative! Try to find something that might be interesting to you. After you write your question, also indicate the techniques you would use to answer it. For this Discussion, you don't need to analyze the data. You only need to develop a research question. 2) The first part of this project involves selecting an appropriate research question and data source. This means you need to select a research question that can be answered using a t-test and selecting a data file, website with appropriate data available, or developing a plan for collecting the data yourself. Normally, another option would be to conduct a survey. How should you proceed with selecting a topic? Follow this criteria before you pose your research question and data source. Look at the resources contained in the documents below. Review the sample projects. Give serious thought about your own interests. Most important... Be original! 1. The 1-sample t-test Required elements: one population, one quantitative variable, a specific value for hypothesis Example scenario: Population: All 2-bedroom apartments in Lumpkin County Variable: monthly rent Research question: Is the average rent for a 2 bedroom apartment in Lumpkin County more than $600 per month? Hypothesis and rationale: \"I predicted that the average monthly rent for a twobedroom apartment in Lumpkin County would be higher than $600. A college planning guide stated that students could probably share a 2-bedroom apartment off campus \"for about $600 a month.\" Based on casual observation, I believe that on average, this estimate is too low.\" 2. The matched pairs t-test Required elements: a) one quantitative variable and two populations in which individuals can be matched OR b) one population and two quantitative variable values for each individual For both (a) and (b) the hypothesis is about the computed difference between the two related values Example scenario for (a): Populations: All canned vegetables sold at Kroger; all canned vegetables sold at Wal-Mart Variable: price (*specifically, the difference in price charged for identical items at each store) Research question: On average, are canned vegetables cheaper at Wal-Mart than at Kroger? Hypothesis and rationale: \"We predicted that on average, Wal-Mart would charge less for the same canned vegetable item. This prediction is based on the general observation that things seem to cost less at Wal-Mart.\" Example scenario for (b): Population: All NGCSU students Variables: rating (1 - 10) of the taste of Coke; and rating (1-10) of the taste of Pepsi (*specifically, taste tests are conducted \"blind\" and the difference in ratings is computed for each participant) Research question: On average, do NGCSU students prefer Coke over Pepsi? Hypothesis and rationale: \" We predicted that on average NGCSU students would rate Coke better in taste than Pepsi. This prediction is based on the fact that in such close proximity to Atlanta, the Coca Cola capital, Coke is often the preferred soft drink.\" 3. The 2-sample t-test (independent samples) Required elements: two populations, one variable Example scenario: Populations: 1) All current NFC football players; 2) All current AFC football players Variable: age Research question: Is there a significant difference between the average age of NFC players and AFC players? (by \"significant\" we mean statistically significant) Hypothesis and rationale: \"We predicted that there might be a difference between the average age of NFC and AFC players. In recent years, the AFC has been perceived as the stronger conference; one could theorize that on average, they have older players who are wiser and more experienced; OR one could theorize that on average, they have younger players who are in better shape and have more stamina. The purpose of this study is to determine if any such age discrepancy exists.\" ProjectPlan:t-Test A. Type of statistical test you plan to conduct(check one, and give relevant details) 1-samplet-test a) Target population: b) Research variable: c) Research question: d) Expected result: matched pairst-test a) Target population(s): b) There search variable will be the difference between and c) Research question: d) Expectedresult: 2-samplet-test a) Targetpopulations(2): b) Research variable: c) Research question: d) Expectedresult: B. Data collection plan(check one,and give relevant details) I will use data from a file. Give name of file and details below. Iwillobtainvdata from a website(s). Give Name of website(s), full URLsand details below. Other data collection plan:Give specific details below. 1) A random and independently chosen sample of four bags of horse carots,each bag labled 20 pounds, had wight of 20.3 , 19.6 , 20.7, 20.0 pounds.assume that the distribution of weights in the population is normal. Find test statistic... t= 0.64 Find p-value....p = 0.565 \f\f\f\f\fMen Centimete rs Centimete (measure rs d) (believed) 168 167.64 171 175.26 182 185.42 168 170.18 189 195.58 174 170.18 172 175.26 193 193.04 177 175.26 177 172.72 180 182.88 173 177.8 173 170.18 168 170.18 186 182.88 \fLongboar Shortboar d d 10 6 22 14 11 9 7 10 15 5 19 7 19 4 21 7 7 6 20 11 21 15 8 12 7 14 10 5 8 16 13 14 15 3 5 3 21 10 6 11 16 15 22 3 9 19 5 6 6 7 16 3 17 9 18 3 20 6 11 11 \f\f\f\f98.4 98.9 99 96.1 98.3 98.9 97.9 99.3 98.5 97.7 \f\f\f\f\f\f\f\fAge (years) Groom Bride 26 34 28 20 30 29 44 40 21 44 30 28 18 24 25 33 28 23 23 26 19 24 18 21 26 24 27 30 32 29 32 27 28 22 20 33 26 38 40 21 47 25 23 20 21 24 27 23 23 20 26 22 25 17 23 25 25 22 26 28 23 27 \f\f\f\f\f\fLongboar Shortboar d d 21 4 13 4 22 9 9 3 5 17 12 4 15 11 15 9 16 6 22 10 8 16 5 14 10 6 13 3 6 12 14 10 9 19 11 5 21 6 5 10 18 4 10 18 9 16 18 15 6 15 5 18 12 9 6 16 6 3 13 6 1. The 1-sample t-test Required elements: one population, one quantitative variable, a specific value for hypothesis Example scenario: Population: All 2-bedroom apartments in Lumpkin County Variable: monthly rent Research question: Is the average rent for a 2 bedroom apartment in Lumpkin County more than $600 per month? Hypothesis and rationale: \"I predicted that the average monthly rent for a twobedroom apartment in Lumpkin County would be higher than $600. A college planning guide stated that students could probably share a 2-bedroom apartment off campus \"for about $600 a month.\" Based on casual observation, I believe that on average, this estimate is too low.\" 2. The matched pairs t-test Required elements: a) one quantitative variable and two populations in which individuals can be matched OR b) one population and two quantitative variable values for each individual For both (a) and (b) the hypothesis is about the computed difference between the two related values Example scenario for (a): Populations: All canned vegetables sold at Kroger; all canned vegetables sold at Wal-Mart Variable: price (*specifically, the difference in price charged for identical items at each store) Research question: On average, are canned vegetables cheaper at Wal-Mart than at Kroger? Hypothesis and rationale: \"We predicted that on average, Wal-Mart would charge less for the same canned vegetable item. This prediction is based on the general observation that things seem to cost less at Wal-Mart.\" Example scenario for (b): Population: All NGCSU students Variables: rating (1 - 10) of the taste of Coke; and rating (1-10) of the taste of Pepsi (*specifically, taste tests are conducted \"blind\" and the difference in ratings is computed for each participant) Research question: On average, do NGCSU students prefer Coke over Pepsi? Hypothesis and rationale: \" We predicted that on average NGCSU students would rate Coke better in taste than Pepsi. This prediction is based on the fact that in such close proximity to Atlanta, the Coca Cola capital, Coke is often the preferred soft drink.\" 3. The 2-sample t-test (independent samples) Required elements: two populations, one variable Example scenario: Populations: 1) All current NFC football players; 2) All current AFC football players Variable: age Research question: Is there a significant difference between the average age of NFC players and AFC players? (by \"significant\" we mean statistically significant) Hypothesis and rationale: \"We predicted that there might be a difference between the average age of NFC and AFC players. In recent years, the AFC has been perceived as the stronger conference; one could theorize that on average, they have older players who are wiser and more experienced; OR one could theorize that on average, they have younger players who are in better shape and have more stamina. The purpose of this study is to determine if any such age discrepancy exists.\" Look at the resources contained in the documents below. Review the sample projects. Give serious thought about your own interests. Most important...Be original! Choose a research question that can be addressed using a t-test. Ensure your research question allows you to collect data to analyze. Devise a plan to collect your data. Submit a project plan form before you submit the project By now, you should have developed a research question, selected a data source, and submitted your project plan .Once your research question and data collection plan are approved, carry out your research. Collect data Conduct t-test analysis, using guidelines in the instructions provided Write your results in a report, using the outline provided Monitor the rubric to make sure you fulfill all project the requirements ProjectPlan:t-Test A. Type ofstatistical testyou planto conduct(check one, and giverelevantdetails) 1-samplet-test a) Targetpopulation: b) Research variable: c) Research question: d) Expectedresult: matched pairst-test a) Targetpopulation(s): b) Theresearch variable willbe thedifference between and c) Research question: d) Expectedresult: 2-samplet-test a) Targetpopulations(2): b) Research variable: c) Research question: d) Expectedresult: B. Data collection plan(check one,and give relevant details) I will use data from a file. Give name of file and details below. Iwillobtaindata froma website(s). Give Name of website(s), full URLsand details below. Otherdata collection plan:Give specific detailsbelow. \f\fMen Centimete rs Centimete (measure rs d) (believed) 168 167.64 171 175.26 182 185.42 168 170.18 189 195.58 174 170.18 172 175.26 193 193.04 177 175.26 177 172.72 180 182.88 173 177.8 173 170.18 168 170.18 186 182.88 \fLongboar Shortboar d d 10 6 22 14 11 9 7 10 15 5 19 7 19 4 21 7 7 6 20 11 21 15 8 12 7 14 10 5 8 16 13 14 15 3 5 3 21 10 6 11 16 15 22 3 9 19 5 6 6 7 16 3 17 9 18 3 20 6 11 11 \f\f\f\f98.4 98.9 99 96.1 98.3 98.9 97.9 99.3 98.5 97.7 \f\f\f\f\f\f\f\fAge (years) Groom Bride 26 34 28 20 30 29 44 40 21 44 30 28 18 24 25 33 28 23 23 26 19 24 18 21 26 24 27 30 32 29 32 27 28 22 20 33 26 38 40 21 47 25 23 20 21 24 27 23 23 20 26 22 25 17 23 25 25 22 26 28 23 27 \f\f\f\f\f\fLongboar Shortboar d d 21 4 13 4 22 9 9 3 5 17 12 4 15 11 15 9 16 6 22 10 8 16 5 14 10 6 13 3 6 12 14 10 9 19 11 5 21 6 5 10 18 4 10 18 9 16 18 15 6 15 5 18 12 9 6 16 6 3 13 6 1. The 1-sample t-test Required elements: one population, one quantitative variable, a specific value for hypothesis Example scenario: Population: All 2-bedroom apartments in Lumpkin County Variable: monthly rent Research question: Is the average rent for a 2 bedroom apartment in Lumpkin County more than $600 per month? Hypothesis and rationale: \"I predicted that the average monthly rent for a twobedroom apartment in Lumpkin County would be higher than $600. A college planning guide stated that students could probably share a 2-bedroom apartment off campus \"for about $600 a month.\" Based on casual observation, I believe that on average, this estimate is too low.\" 2. The matched pairs t-test Required elements: a) one quantitative variable and two populations in which individuals can be matched OR b) one population and two quantitative variable values for each individual For both (a) and (b) the hypothesis is about the computed difference between the two related values Example scenario for (a): Populations: All canned vegetables sold at Kroger; all canned vegetables sold at Wal-Mart Variable: price (*specifically, the difference in price charged for identical items at each store) Research question: On average, are canned vegetables cheaper at Wal-Mart than at Kroger? Hypothesis and rationale: \"We predicted that on average, Wal-Mart would charge less for the same canned vegetable item. This prediction is based on the general observation that things seem to cost less at Wal-Mart.\" Example scenario for (b): Population: All NGCSU students Variables: rating (1 - 10) of the taste of Coke; and rating (1-10) of the taste of Pepsi (*specifically, taste tests are conducted \"blind\" and the difference in ratings is computed for each participant) Research question: On average, do NGCSU students prefer Coke over Pepsi? Hypothesis and rationale: \" We predicted that on average NGCSU students would rate Coke better in taste than Pepsi. This prediction is based on the fact that in such close proximity to Atlanta, the Coca Cola capital, Coke is often the preferred soft drink.\" 3. The 2-sample t-test (independent samples) Required elements: two populations, one variable Example scenario: Populations: 1) All current NFC football players; 2) All current AFC football players Variable: age Research question: Is there a significant difference between the average age of NFC players and AFC players? (by \"significant\" we mean statistically significant) Hypothesis and rationale: \"We predicted that there might be a difference between the average age of NFC and AFC players. In recent years, the AFC has been perceived as the stronger conference; one could theorize that on average, they have older players who are wiser and more experienced; OR one could theorize that on average, they have younger players who are in better shape and have more stamina. The purpose of this study is to determine if any such age discrepancy exists.\" Look at the resources contained in the documents below. Review the sample projects. Give serious thought about your own interests. Most important...Be original! Choose a research question that can be addressed using a t-test. Ensure your research question allows you to collect data to analyze. Devise a plan to collect your data. Submit a project plan form before you submit the project By now, you should have developed a research question, selected a data source, and submitted your project plan .Once your research question and data collection plan are approved, carry out your research. Collect data Conduct t-test analysis, using guidelines in the instructions provided Write your results in a report, using the outline provided Monitor the rubric to make sure you fulfill all project the requirements ProjectPlan:t-Test A. Type ofstatistical testyou planto conduct(check one, and giverelevantdetails) 1-samplet-test a) Targetpopulation: b) Research variable: c) Research question: d) Expectedresult: matched pairst-test a) Targetpopulation(s): b) Theresearch variable willbe thedifference between and c) Research question: d) Expectedresult: 2-samplet-test a) Targetpopulations(2): b) Research variable: c) Research question: d) Expectedresult: B. Data collection plan(check one,and give relevant details) I will use data from a file. Give name of file and details below. Iwillobtaindata froma website(s). Give Name of website(s), full URLsand details below. Otherdata collection plan:Give specific detailsbelow