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Explanation & Answer
Here, 3x-4*11=26
=> 3x = 44+26
=>3x= 70
So, x= 23.33 (Answer)
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Regression Analysis Paper
This is a university senior level paper. The topic is about regression analysis and I put the project proposal below and y ...
Regression Analysis Paper
This is a university senior level paper. The topic is about regression analysis and I put the project proposal below and you can see the guideline what would like to see on paper below too.proposal Regression analysis is used in various ways in various fields. In recent years, with the advent of smart devices, human beings have become able to accumulate and process more data, so regression analysis has become more popular. It is used in various names; data science, big data, artificial intelligence, machine learning and so on. We trust the conclusions obtained through this analysis and this conclusion serves as a compass for our decisions. However, this conclusion has limitations and I would like to discuss these limitations through this project.what i would appreciate if i see these from the paper:- the popularity of regression analysis from the real world. like big data, data mining...- the strengths of this analysis, why it is popular now and why now compared to the past?- the limitations of this analysis. for example, causation versus correlation, in-data versus outside of data...etc- how to mitigate the limitations-conclusion
Cuyamaca College Statistics Lab Exam
Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you ...
Cuyamaca College Statistics Lab Exam
Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you will be expected to complete more extensive labs and in-class quizzes/exams using the skills learned in these early mini-labs.Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Here are the directions, grading rubric, and definition of high-quality feedback for the Learn by Doing discussion board exercises. A list of StatCrunch directions is provided at the bottom of this page. But, here is a brief introduction to the statistical software on how to upload data.ContextWe will use the Best Actor Oscar winners (1970–2001) data file to learn how to create a histogram using StatCrunch, and to practice what we've learned about describing a histogram. We are interested in describing the distribution of actors' ages when they won the Best Actor Oscar.DataStart by downloading the actor datafile to your computer.Here are the directions for downloading the datafile.Here is the actor (Links to an external site.) datafile. (This is the "Excel" file.)Next you will create a histogram of the ages of Best Oscar winners and upload your histogram to your Stats-Class folder in Canvas. Here are the steps.Login and open StatCrunch (directions).Upload the ages data file to StatCrunch (directions).Create a histogram of the ages of Best Actor Oscar winners (directions).Download the StatCrunch output window, your histogram (directions).Store your histogram (the .png file) in your Stats-Class folder (directions).PromptIn your initial post, respond to the following discussion prompt. Describe the distribution of ages of the Best Actor Oscar winners. Your description should include: shape, center (a typical representative age), a typical interval of representative ages, spread (overall range of ages), and any outliers (unusual ages). Be sure to embed your histogram in your initial post (directions). Please do not submit your histogram as an attachment.Create a second histogram for the distribution of ages, and adjust the bin width (directions). Try both smaller and larger bin widths. Choose a bin width so that your second histogram does not look like the first. Upload your second histogram to your Stats-Class folder. Also embed your second histogram with your initial post. Indicate which histogram is better for analyzing the data (your first embedded histogram or your second). Explain why.List of StatCrunch DirectionsEach link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion. Create Your Stats-Class Folder in Canvas (You only need to do this once.)Purchase StatCrunch (You only need to do this once.)Open StatCrunchDownload Excel Data FileUpload Excel Data File to StatCrunchDownload StatCrunch Output Window (no screenshots; please use these directions)Upload Files into Your Stat-Class Folder in CanvasEmbed Pictures in a Discussion Post (no attachments; please use these directions)Create a HistogramAdjust Histogram Bin WidthHere is a PDF document with all StatCrunch directions (Links to an external site.).
Purdue Global University Unit 5 Statistical Reasoning Questions
In Unit 5, there are three main topics (problem types): describing correlations, measuring correlations (with the r value) ...
Purdue Global University Unit 5 Statistical Reasoning Questions
In Unit 5, there are three main topics (problem types): describing correlations, measuring correlations (with the r value), and creating and evaluating scatterplots. You will be exposed to all three topics, and will have the opportunity to discuss and compare these topics with your fellow learners.Using any Excel dataset, choose two quantitative variables from the dataset. For example, you might choose “age” and “weight.” Next, do the following:What is the name of the dataset you have chosen? What are the names of the two quantitative variables you are investigating?Using Excel, calculate the relationship (correlation) between these two variables. Write down your calculated r value.Given the r value you calculated in number 1 above, explain what the r value tells you about the relationship between the two variables. For example, is the relationship positive or negative? Is the relationship strong, medium, or weak?Using the two variables you have chosen, create and attach to your post a scatterplot. Does the scatterplot have a linear appearance? What does the scatterplot tell you about the relationship between your two variables?Please create personalized and substantive responses to at least two other student main posts. In your response, include the following:Choose any two classmates and review their main posts.Find the dataset that each student used, and repeat their r value calculation in Excel for the variables they chose. Are they correct? Do you agree with how they described the relationship between the two variables? Explain in one paragraph and include both your results and the student results.For the same two classmates, also review their scatterplots. Discuss the “shape” of the scatterplot - is it mostly linear or is it all scattered around? Does the scatterplot seem to have a positive (upwards from left to right) or negative slope? Does their scatterplot visually match what the r value is suggesting? What can you say about the relationship based on the scatterplot?Discussion RequirementsReading and ResourcesRead the assigned chapters from the following textbooks:Bennett, J., Briggs, W.L. & Triola, M.F. (2013) Statistical Reasoning for Everyday Life (4th ed.). Upper Saddle, NJ: Pearson.Chapter 7: “Correlation and Causality”Reading the textbook and reviewing the textbook examples are excellent methods for starting each unit. Reading the textbook offers context and explanations for new concepts and methods. Completing the textbook examples on paper (and with Excel) is a great way to practice and learn the new methods and concepts introduced. Student feedback has suggested that reading the textbook and practicing the textbook examples has been particularly helpful if completed before the unit Seminar. Some students have reported that keeping a notebook handy, and recording new definitions or concepts encountered while reading is helpful, more organized, and stress reducing.This chapter includes a section that offers examples using technologies such as Excel. In addition, at the end of each chapter section, or at the end of the chapter, are review exercises that are very helpful for practicing and preparing.In this course, students may use Excel for any statistical calculations. Excel can be used to evaluate data in many ways. Excel can be used to calculate numerical measures, such as measures of center (such as mean and median) and measures of variation (variance, standard deviation, and range), as well as many other measures such as min, max, and correlation (r-value). Excel can also be used to create visualizations, such as histograms, bar graphs, pie graphs, scatterplots, and others. Excel may also be used to create linear regression equations. Because Excel is a very common tool, the Internet and YouTube both contain considerable support resources and tutorials. TEXTBOOKSBennett, J., Briggs, W., Triola, M. (2014) Statistical Reasoning: For Everyday Life.(4th ed)
STAT 200 University of Baltimore Week 6 Statistics Questions
STAT 200 Week 6 Homework Problems9.1.2Many high school students take the AP tests in different subject areas.In 2007, of t ...
STAT 200 University of Baltimore Week 6 Statistics Questions
STAT 200 Week 6 Homework Problems9.1.2Many high school students take the AP tests in different subject areas.In 2007, of the 144,796 students who took the biology exam 84,199 of them were female.In that same year, of the 211,693 students who took the calculus AB exam 102,598 of them were female ("AP exam scores," 2013).Estimate the difference in the proportion of female students taking the biology exam and female students taking the calculus AB exam using a 90% confidence level.9.1.5Are there more children diagnosed with Autism Spectrum Disorder (ASD) in states that have larger urban areas over states that are mostly rural?In the state of Pennsylvania, a fairly urban state, there are 245 eight year olds diagnosed with ASD out of 18,440 eight year olds evaluated.In the state of Utah, a fairly rural state, there are 45 eight year olds diagnosed with ASD out of 2,123 eight year olds evaluated ("Autism and developmental," 2008).Is there enough evidence to show that the proportion of children diagnosed with ASD in Pennsylvania is more than the proportion in Utah?Test at the 1% level.9.2.3All Fresh Seafood is a wholesale fish company based on the east coast of the U.S.Catalina Offshore Products is a wholesale fish company based on the west coast of the U.S.Table #9.2.5 contains prices from both companies for specific fish types ("Seafood online," 2013) ("Buy sushi grade," 2013).Do the data provide enough evidence to show that a west coast fish wholesaler is more expensive than an east coast wholesaler?Test at the 5% level.Table #9.2.5: Wholesale Prices of Fish in Dollars Fish All Fresh Seafood Prices Catalina Offshore Products Prices Cod 19.99 17.99 Tilapi 6.00 13.99 Farmed Salmon 19.99 22.99 Organic Salmon 24.99 24.99 Grouper Fillet 29.99 19.99 Tuna 28.99 31.99 Swordfish 23.99 23.99 Sea Bass 32.99 23.99 Striped Bass 29.99 14.99 9.2.6The British Department of Transportation studied to see if people avoid driving on Friday the 13th.They did a traffic count on a Friday and then again on a Friday the 13th at the same two locations ("Friday the 13th," 2013).The data for each location on the two different dates is in table #9.2.6.Estimate the mean difference in traffic count between the 6th and the 13th using a 90% level.Table #9.2.6: Traffic Count Dates 6th 13th 1990, July 139246 138548 1990, July 134012 132908 1991, September 137055 136018 1991, September 133732 131843 1991, December 123552 121641 1991, December 121139 118723 1992, March 128293 125532 1992, March 124631 120249 1992, November 124609 122770 1992, November 117584 117263 9.3.1The income of males in each state of the United States, including the District of Columbia and Puerto Rico, are given in table #9.3.3, and the income of females is given in table #9.3.4 ("Median income of," 2013).Is there enough evidence to show that the mean income of males is more than of females?Test at the 1% level.Table #9.3.3: Data of Income for Males $42,951 $52,379 $42,544 $37,488 $49,281 $50,987 $60,705 $50,411 $66,760 $40,951 $43,902 $45,494 $41,528 $50,746 $45,183 $43,624 $43,993 $41,612 $46,313 $43,944 $56,708 $60,264 $50,053 $50,580 $40,202 $43,146 $41,635 $42,182 $41,803 $53,033 $60,568 $41,037 $50,388 $41,950 $44,660 $46,176 $41,420 $45,976 $47,956 $22,529 $48,842 $41,464 $40,285 $41,309 $43,160 $47,573 $44,057 $52,805 $53,046 $42,125 $46,214 $51,630 Table #9.3.4: Data of Income for Females $31,862 $40,550 $36,048 $30,752 $41,817 $40,236 $47,476 $40,500 $60,332 $33,823 $35,438 $37,242 $31,238 $39,150 $34,023 $33,745 $33,269 $32,684 $31,844 $34,599 $48,748 $46,185 $36,931 $40,416 $29,548 $33,865 $31,067 $33,424 $35,484 $41,021 $47,155 $32,316 $42,113 $33,459 $32,462 $35,746 $31,274 $36,027 $37,089 $22,117 $41,412 $31,330 $31,329 $33,184 $35,301 $32,843 $38,177 $40,969 $40,993 $29,688 $35,890 $34,381 9.3.3A study was conducted that measured the total brain volume (TBV) (in ) of patients that had schizophrenia and patients that are considered normal.Table #9.3.5 contains the TBV of the normal patients and table #9.3.6 contains the TBV of schizophrenia patients ("SOCR data oct2009," 2013).Is there enough evidence to show that the patients with schizophrenia have less TBV on average than a patient that is considered normal?Test at the 10% level.Table #9.3.5: Total Brain Volume (in ) of Normal Patients 1663407 1583940 1299470 1535137 1431890 1578698 1453510 1650348 1288971 1366346 1326402 1503005 1474790 1317156 1441045 1463498 1650207 1523045 1441636 1432033 1420416 1480171 1360810 1410213 1574808 1502702 1203344 1319737 1688990 1292641 1512571 1635918 Table #9.3.6: Total Brain Volume (in ) of Schizophrenia Patients 1331777 1487886 1066075 1297327 1499983 1861991 1368378 1476891 1443775 1337827 1658258 1588132 1690182 1569413 1177002 1387893 1483763 1688950 1563593 1317885 1420249 1363859 1238979 1286638 1325525 1588573 1476254 1648209 1354054 1354649 1636119 9.3.4A study was conducted that measured the total brain volume (TBV) (in ) of patients that had schizophrenia and patients that are considered normal.Table #9.3.5 contains the TBV of the normal patients and table #9.3.6 contains the TBV of schizophrenia patients ("SOCR data oct2009," 2013).Compute a 90% confidence interval for the difference in TBV of normal patients and patients with Schizophrenia. 9.3.8The number of cell phones per 100 residents in countries in Europe is given in table #9.3.9 for the year 2010.The number of cell phones per 100 residents in countries of the Americas is given in table #9.3.10 also for the year 2010 ("Population reference bureau," 2013).Find the 98% confidence interval for the different in mean number of cell phones per 100 residents in Europe and the Americas.Table #9.3.9: Number of Cell Phones per 100 Residents in Europe 100 76 100 130 75 84 112 84 138 133 118 134 126 188 129 93 64 128 124 122 109 121 127 152 96 63 99 95 151 147 123 95 67 67 118 125 110 115 140 115 141 77 98 102 102 112 118 118 54 23 121 126 47 Table #9.3.10: Number of Cell Phones per 100 Residents in the Americas 158 117 106 159 53 50 78 66 88 92 42 3 150 72 86 113 50 58 70 109 37 32 85 101 75 69 55 115 95 73 86 157 100 119 81 113 87 105 96 11.3.2Levi-Strauss Co manufactures clothing.The quality control department measures weekly values of different suppliers for the percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up).The data is in table #11.3.3, and there are some negative values because sometimes the supplier is able to layout the pattern better than the computer ("Waste run up," 2013).Do the data show that there is a difference between some of the suppliers?Test at the 1% level.Table #11.3.3: Run-ups for Different Plants Making Levi Strauss Clothing Plant 1 Plant 2 Plant 3 Plant 4 Plant 5 1.2 16.4 12.1 11.5 24 10.1 -6 9.7 10.2 -3.7 -2 -11.6 7.4 3.8 8.2 1.5 -1.3 -2.1 8.3 9.2 -3 4 10.1 6.6 -9.3 -0.7 17 4.7 10.2 8 3.2 3.8 4.6 8.8 15.8 2.7 4.3 3.9 2.7 22.3 -3.2 10.4 3.6 5.1 3.1 -1.7 4.2 9.6 11.2 16.8 2.4 8.5 9.8 5.9 11.3 0.3 6.3 6.5 13 12.3 3.5 9 5.7 6.8 16.9 -0.8 7.1 5.1 14.5 19.4 4.3 3.4 5.2 2.8 19.7 -0.8 7.3 13 3 -3.9 7.1 42.7 7.6 0.9 3.4 1.4 70.2 1.5 0.7 3 8.5 2.4 6 1.3 2.9 11.3.4A study was undertaken to see how accurate food labeling for calories on food that is considered reduced calorie.The group measured the amount of calories for each item of food and then found the percent difference between measured and labeled food, .The group also looked at food that was nationally advertised, regionally distributed, or locally prepared.The data is in table #11.3.5 ("Calories datafile," 2013).Do the data indicate that at least two of the mean percent differences between the three groups are different?Test at the 10% level.Table #11.3.5: Percent Differences Between Measured and Labeled Food National Advertised Regionally Distributed Locally Prepared 2 41 15 -28 46 60 -6 2 250 8 25 145 6 39 6 -1 16.5 80 10 17 95 13 28 3 15 -3 -4 14 -4 34 -18 42 10 5 3 -7 3 -0.5 -10 6
Northwestern Technical College Handicap Archery League Problem Worksheet
1. My archery league allows some archers to have a handicap in the third week of shooting. A perfect score is 300. Anyon ...
Northwestern Technical College Handicap Archery League Problem Worksheet
1. My archery league allows some archers to have a handicap in the third week of shooting. A perfect score is 300. Anyone who shoots lower than 290 in either of the first two weeks gets a handicap of half the difference between a perfect score and the score they shot during the second week. Everyone else gets a handicap of0. Open the excel workbook Archery. Label column D Handicap. In column D have excel compute each archer's handicap.
Testing Hypotheses for Means.
Review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tes ...
Testing Hypotheses for Means.
Review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tests:Independent sample t testPaired sample t testOne sample t testBased on each of the three research scenarios provided, open the High School Longitudinal Study dataset or the Afrobarometer dataset from this week’s Learning Resources using SPSS software, then choose and run the appropriate t test.For this Assignment:Write a 2- to 3-paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output. Based on your results, provide an explanation of what the implications of social change might be.Use proper APA format, citations, and referencing for your analysis, research questions, and output.
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Regression Analysis Paper
This is a university senior level paper. The topic is about regression analysis and I put the project proposal below and y ...
Regression Analysis Paper
This is a university senior level paper. The topic is about regression analysis and I put the project proposal below and you can see the guideline what would like to see on paper below too.proposal Regression analysis is used in various ways in various fields. In recent years, with the advent of smart devices, human beings have become able to accumulate and process more data, so regression analysis has become more popular. It is used in various names; data science, big data, artificial intelligence, machine learning and so on. We trust the conclusions obtained through this analysis and this conclusion serves as a compass for our decisions. However, this conclusion has limitations and I would like to discuss these limitations through this project.what i would appreciate if i see these from the paper:- the popularity of regression analysis from the real world. like big data, data mining...- the strengths of this analysis, why it is popular now and why now compared to the past?- the limitations of this analysis. for example, causation versus correlation, in-data versus outside of data...etc- how to mitigate the limitations-conclusion
Cuyamaca College Statistics Lab Exam
Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you ...
Cuyamaca College Statistics Lab Exam
Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you will be expected to complete more extensive labs and in-class quizzes/exams using the skills learned in these early mini-labs.Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Here are the directions, grading rubric, and definition of high-quality feedback for the Learn by Doing discussion board exercises. A list of StatCrunch directions is provided at the bottom of this page. But, here is a brief introduction to the statistical software on how to upload data.ContextWe will use the Best Actor Oscar winners (1970–2001) data file to learn how to create a histogram using StatCrunch, and to practice what we've learned about describing a histogram. We are interested in describing the distribution of actors' ages when they won the Best Actor Oscar.DataStart by downloading the actor datafile to your computer.Here are the directions for downloading the datafile.Here is the actor (Links to an external site.) datafile. (This is the "Excel" file.)Next you will create a histogram of the ages of Best Oscar winners and upload your histogram to your Stats-Class folder in Canvas. Here are the steps.Login and open StatCrunch (directions).Upload the ages data file to StatCrunch (directions).Create a histogram of the ages of Best Actor Oscar winners (directions).Download the StatCrunch output window, your histogram (directions).Store your histogram (the .png file) in your Stats-Class folder (directions).PromptIn your initial post, respond to the following discussion prompt. Describe the distribution of ages of the Best Actor Oscar winners. Your description should include: shape, center (a typical representative age), a typical interval of representative ages, spread (overall range of ages), and any outliers (unusual ages). Be sure to embed your histogram in your initial post (directions). Please do not submit your histogram as an attachment.Create a second histogram for the distribution of ages, and adjust the bin width (directions). Try both smaller and larger bin widths. Choose a bin width so that your second histogram does not look like the first. Upload your second histogram to your Stats-Class folder. Also embed your second histogram with your initial post. Indicate which histogram is better for analyzing the data (your first embedded histogram or your second). Explain why.List of StatCrunch DirectionsEach link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion. Create Your Stats-Class Folder in Canvas (You only need to do this once.)Purchase StatCrunch (You only need to do this once.)Open StatCrunchDownload Excel Data FileUpload Excel Data File to StatCrunchDownload StatCrunch Output Window (no screenshots; please use these directions)Upload Files into Your Stat-Class Folder in CanvasEmbed Pictures in a Discussion Post (no attachments; please use these directions)Create a HistogramAdjust Histogram Bin WidthHere is a PDF document with all StatCrunch directions (Links to an external site.).
Purdue Global University Unit 5 Statistical Reasoning Questions
In Unit 5, there are three main topics (problem types): describing correlations, measuring correlations (with the r value) ...
Purdue Global University Unit 5 Statistical Reasoning Questions
In Unit 5, there are three main topics (problem types): describing correlations, measuring correlations (with the r value), and creating and evaluating scatterplots. You will be exposed to all three topics, and will have the opportunity to discuss and compare these topics with your fellow learners.Using any Excel dataset, choose two quantitative variables from the dataset. For example, you might choose “age” and “weight.” Next, do the following:What is the name of the dataset you have chosen? What are the names of the two quantitative variables you are investigating?Using Excel, calculate the relationship (correlation) between these two variables. Write down your calculated r value.Given the r value you calculated in number 1 above, explain what the r value tells you about the relationship between the two variables. For example, is the relationship positive or negative? Is the relationship strong, medium, or weak?Using the two variables you have chosen, create and attach to your post a scatterplot. Does the scatterplot have a linear appearance? What does the scatterplot tell you about the relationship between your two variables?Please create personalized and substantive responses to at least two other student main posts. In your response, include the following:Choose any two classmates and review their main posts.Find the dataset that each student used, and repeat their r value calculation in Excel for the variables they chose. Are they correct? Do you agree with how they described the relationship between the two variables? Explain in one paragraph and include both your results and the student results.For the same two classmates, also review their scatterplots. Discuss the “shape” of the scatterplot - is it mostly linear or is it all scattered around? Does the scatterplot seem to have a positive (upwards from left to right) or negative slope? Does their scatterplot visually match what the r value is suggesting? What can you say about the relationship based on the scatterplot?Discussion RequirementsReading and ResourcesRead the assigned chapters from the following textbooks:Bennett, J., Briggs, W.L. & Triola, M.F. (2013) Statistical Reasoning for Everyday Life (4th ed.). Upper Saddle, NJ: Pearson.Chapter 7: “Correlation and Causality”Reading the textbook and reviewing the textbook examples are excellent methods for starting each unit. Reading the textbook offers context and explanations for new concepts and methods. Completing the textbook examples on paper (and with Excel) is a great way to practice and learn the new methods and concepts introduced. Student feedback has suggested that reading the textbook and practicing the textbook examples has been particularly helpful if completed before the unit Seminar. Some students have reported that keeping a notebook handy, and recording new definitions or concepts encountered while reading is helpful, more organized, and stress reducing.This chapter includes a section that offers examples using technologies such as Excel. In addition, at the end of each chapter section, or at the end of the chapter, are review exercises that are very helpful for practicing and preparing.In this course, students may use Excel for any statistical calculations. Excel can be used to evaluate data in many ways. Excel can be used to calculate numerical measures, such as measures of center (such as mean and median) and measures of variation (variance, standard deviation, and range), as well as many other measures such as min, max, and correlation (r-value). Excel can also be used to create visualizations, such as histograms, bar graphs, pie graphs, scatterplots, and others. Excel may also be used to create linear regression equations. Because Excel is a very common tool, the Internet and YouTube both contain considerable support resources and tutorials. TEXTBOOKSBennett, J., Briggs, W., Triola, M. (2014) Statistical Reasoning: For Everyday Life.(4th ed)
STAT 200 University of Baltimore Week 6 Statistics Questions
STAT 200 Week 6 Homework Problems9.1.2Many high school students take the AP tests in different subject areas.In 2007, of t ...
STAT 200 University of Baltimore Week 6 Statistics Questions
STAT 200 Week 6 Homework Problems9.1.2Many high school students take the AP tests in different subject areas.In 2007, of the 144,796 students who took the biology exam 84,199 of them were female.In that same year, of the 211,693 students who took the calculus AB exam 102,598 of them were female ("AP exam scores," 2013).Estimate the difference in the proportion of female students taking the biology exam and female students taking the calculus AB exam using a 90% confidence level.9.1.5Are there more children diagnosed with Autism Spectrum Disorder (ASD) in states that have larger urban areas over states that are mostly rural?In the state of Pennsylvania, a fairly urban state, there are 245 eight year olds diagnosed with ASD out of 18,440 eight year olds evaluated.In the state of Utah, a fairly rural state, there are 45 eight year olds diagnosed with ASD out of 2,123 eight year olds evaluated ("Autism and developmental," 2008).Is there enough evidence to show that the proportion of children diagnosed with ASD in Pennsylvania is more than the proportion in Utah?Test at the 1% level.9.2.3All Fresh Seafood is a wholesale fish company based on the east coast of the U.S.Catalina Offshore Products is a wholesale fish company based on the west coast of the U.S.Table #9.2.5 contains prices from both companies for specific fish types ("Seafood online," 2013) ("Buy sushi grade," 2013).Do the data provide enough evidence to show that a west coast fish wholesaler is more expensive than an east coast wholesaler?Test at the 5% level.Table #9.2.5: Wholesale Prices of Fish in Dollars Fish All Fresh Seafood Prices Catalina Offshore Products Prices Cod 19.99 17.99 Tilapi 6.00 13.99 Farmed Salmon 19.99 22.99 Organic Salmon 24.99 24.99 Grouper Fillet 29.99 19.99 Tuna 28.99 31.99 Swordfish 23.99 23.99 Sea Bass 32.99 23.99 Striped Bass 29.99 14.99 9.2.6The British Department of Transportation studied to see if people avoid driving on Friday the 13th.They did a traffic count on a Friday and then again on a Friday the 13th at the same two locations ("Friday the 13th," 2013).The data for each location on the two different dates is in table #9.2.6.Estimate the mean difference in traffic count between the 6th and the 13th using a 90% level.Table #9.2.6: Traffic Count Dates 6th 13th 1990, July 139246 138548 1990, July 134012 132908 1991, September 137055 136018 1991, September 133732 131843 1991, December 123552 121641 1991, December 121139 118723 1992, March 128293 125532 1992, March 124631 120249 1992, November 124609 122770 1992, November 117584 117263 9.3.1The income of males in each state of the United States, including the District of Columbia and Puerto Rico, are given in table #9.3.3, and the income of females is given in table #9.3.4 ("Median income of," 2013).Is there enough evidence to show that the mean income of males is more than of females?Test at the 1% level.Table #9.3.3: Data of Income for Males $42,951 $52,379 $42,544 $37,488 $49,281 $50,987 $60,705 $50,411 $66,760 $40,951 $43,902 $45,494 $41,528 $50,746 $45,183 $43,624 $43,993 $41,612 $46,313 $43,944 $56,708 $60,264 $50,053 $50,580 $40,202 $43,146 $41,635 $42,182 $41,803 $53,033 $60,568 $41,037 $50,388 $41,950 $44,660 $46,176 $41,420 $45,976 $47,956 $22,529 $48,842 $41,464 $40,285 $41,309 $43,160 $47,573 $44,057 $52,805 $53,046 $42,125 $46,214 $51,630 Table #9.3.4: Data of Income for Females $31,862 $40,550 $36,048 $30,752 $41,817 $40,236 $47,476 $40,500 $60,332 $33,823 $35,438 $37,242 $31,238 $39,150 $34,023 $33,745 $33,269 $32,684 $31,844 $34,599 $48,748 $46,185 $36,931 $40,416 $29,548 $33,865 $31,067 $33,424 $35,484 $41,021 $47,155 $32,316 $42,113 $33,459 $32,462 $35,746 $31,274 $36,027 $37,089 $22,117 $41,412 $31,330 $31,329 $33,184 $35,301 $32,843 $38,177 $40,969 $40,993 $29,688 $35,890 $34,381 9.3.3A study was conducted that measured the total brain volume (TBV) (in ) of patients that had schizophrenia and patients that are considered normal.Table #9.3.5 contains the TBV of the normal patients and table #9.3.6 contains the TBV of schizophrenia patients ("SOCR data oct2009," 2013).Is there enough evidence to show that the patients with schizophrenia have less TBV on average than a patient that is considered normal?Test at the 10% level.Table #9.3.5: Total Brain Volume (in ) of Normal Patients 1663407 1583940 1299470 1535137 1431890 1578698 1453510 1650348 1288971 1366346 1326402 1503005 1474790 1317156 1441045 1463498 1650207 1523045 1441636 1432033 1420416 1480171 1360810 1410213 1574808 1502702 1203344 1319737 1688990 1292641 1512571 1635918 Table #9.3.6: Total Brain Volume (in ) of Schizophrenia Patients 1331777 1487886 1066075 1297327 1499983 1861991 1368378 1476891 1443775 1337827 1658258 1588132 1690182 1569413 1177002 1387893 1483763 1688950 1563593 1317885 1420249 1363859 1238979 1286638 1325525 1588573 1476254 1648209 1354054 1354649 1636119 9.3.4A study was conducted that measured the total brain volume (TBV) (in ) of patients that had schizophrenia and patients that are considered normal.Table #9.3.5 contains the TBV of the normal patients and table #9.3.6 contains the TBV of schizophrenia patients ("SOCR data oct2009," 2013).Compute a 90% confidence interval for the difference in TBV of normal patients and patients with Schizophrenia. 9.3.8The number of cell phones per 100 residents in countries in Europe is given in table #9.3.9 for the year 2010.The number of cell phones per 100 residents in countries of the Americas is given in table #9.3.10 also for the year 2010 ("Population reference bureau," 2013).Find the 98% confidence interval for the different in mean number of cell phones per 100 residents in Europe and the Americas.Table #9.3.9: Number of Cell Phones per 100 Residents in Europe 100 76 100 130 75 84 112 84 138 133 118 134 126 188 129 93 64 128 124 122 109 121 127 152 96 63 99 95 151 147 123 95 67 67 118 125 110 115 140 115 141 77 98 102 102 112 118 118 54 23 121 126 47 Table #9.3.10: Number of Cell Phones per 100 Residents in the Americas 158 117 106 159 53 50 78 66 88 92 42 3 150 72 86 113 50 58 70 109 37 32 85 101 75 69 55 115 95 73 86 157 100 119 81 113 87 105 96 11.3.2Levi-Strauss Co manufactures clothing.The quality control department measures weekly values of different suppliers for the percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up).The data is in table #11.3.3, and there are some negative values because sometimes the supplier is able to layout the pattern better than the computer ("Waste run up," 2013).Do the data show that there is a difference between some of the suppliers?Test at the 1% level.Table #11.3.3: Run-ups for Different Plants Making Levi Strauss Clothing Plant 1 Plant 2 Plant 3 Plant 4 Plant 5 1.2 16.4 12.1 11.5 24 10.1 -6 9.7 10.2 -3.7 -2 -11.6 7.4 3.8 8.2 1.5 -1.3 -2.1 8.3 9.2 -3 4 10.1 6.6 -9.3 -0.7 17 4.7 10.2 8 3.2 3.8 4.6 8.8 15.8 2.7 4.3 3.9 2.7 22.3 -3.2 10.4 3.6 5.1 3.1 -1.7 4.2 9.6 11.2 16.8 2.4 8.5 9.8 5.9 11.3 0.3 6.3 6.5 13 12.3 3.5 9 5.7 6.8 16.9 -0.8 7.1 5.1 14.5 19.4 4.3 3.4 5.2 2.8 19.7 -0.8 7.3 13 3 -3.9 7.1 42.7 7.6 0.9 3.4 1.4 70.2 1.5 0.7 3 8.5 2.4 6 1.3 2.9 11.3.4A study was undertaken to see how accurate food labeling for calories on food that is considered reduced calorie.The group measured the amount of calories for each item of food and then found the percent difference between measured and labeled food, .The group also looked at food that was nationally advertised, regionally distributed, or locally prepared.The data is in table #11.3.5 ("Calories datafile," 2013).Do the data indicate that at least two of the mean percent differences between the three groups are different?Test at the 10% level.Table #11.3.5: Percent Differences Between Measured and Labeled Food National Advertised Regionally Distributed Locally Prepared 2 41 15 -28 46 60 -6 2 250 8 25 145 6 39 6 -1 16.5 80 10 17 95 13 28 3 15 -3 -4 14 -4 34 -18 42 10 5 3 -7 3 -0.5 -10 6
Northwestern Technical College Handicap Archery League Problem Worksheet
1. My archery league allows some archers to have a handicap in the third week of shooting. A perfect score is 300. Anyon ...
Northwestern Technical College Handicap Archery League Problem Worksheet
1. My archery league allows some archers to have a handicap in the third week of shooting. A perfect score is 300. Anyone who shoots lower than 290 in either of the first two weeks gets a handicap of half the difference between a perfect score and the score they shot during the second week. Everyone else gets a handicap of0. Open the excel workbook Archery. Label column D Handicap. In column D have excel compute each archer's handicap.
Testing Hypotheses for Means.
Review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tes ...
Testing Hypotheses for Means.
Review the t test scenarios found in this week’s Learning Resources and consider the three different approaches of t tests:Independent sample t testPaired sample t testOne sample t testBased on each of the three research scenarios provided, open the High School Longitudinal Study dataset or the Afrobarometer dataset from this week’s Learning Resources using SPSS software, then choose and run the appropriate t test.For this Assignment:Write a 2- to 3-paragraph analysis of your t test results for each research scenario and include the SPSS syntax and output. Based on your results, provide an explanation of what the implications of social change might be.Use proper APA format, citations, and referencing for your analysis, research questions, and output.
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