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(c) What is the probability of obtaining heads and a two? (Enter the probability as a fraction.)
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Explanation & Answer
c) the probability is the product of single probabilities:
1/2* 1/6 = 1/12
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Week 6: Statistics
It is difficult to watch the news or read the paper without running into statistics. Numbers are used to support claims, report poll results, or sway you to purchase a product via advertising. Most of this data is taken from a sample or small subgroup of the population, which reduces the accuracy. Sampling, or taking data from a subset of the population, creates an opportunity for error, as not everyone in the population is represented. You may have heard a claim made, such as “three out of four dentists recommend White X toothpaste.” This sounds impressive until you learn that these dentists that recommend White X toothpaste are also given hundreds of free samples to share with their clients. These values should be critically examined for bias, bad data collection methods, or the presence of outliers that skew statistics.
This week, you will explore where data comes from, how to organize and summarize data, and how to use this to make decisions.
Discussion: Avoiding Bad Statistics
You may have heard the saying that ‘numbers never lie’. What could be more trustworthy than a solution to a mathematical equation? Enter statistics, an area of mathematics in which numbers can be used to mislead. This can be intentional, as is often the case in advertising campaigns. You might hear claims, such as the best weight loss program in the world will produce an average of 20 pounds of weight loss in the first month. Claims like these usually come with the footnote that "results are not typical" as outliers in data can affect an average value easily. One or two individuals who lost a great deal of weight can make the average value seem more impressive than it is. Misleading statistics can also be unintentional if the researcher does not consider all the important aspects.
For this Discussion, you will explore some critical considerations when assessing the accuracy of statistics.
To prepare for this Discussion:
Imagine you have been hired to complete a data analysis project to promote social change in an area important to you. Some possible topics include public transportation, distribution of public services, health care, public education, or another topic of interest.
View the video on ways to spot bad statistics and reflect on several aspects that Chalabi (2017) indicates are necessary to consider when assessing the accuracy of the values presented. Then, consider how these aspects apply to the topic you selected.
Think about what kinds of data you would collect to present in a memo to your congress person or government representative, regarding the social change you are proposing for your topic, and how you plan to address uncertainty in your results.
Think about how you will make sure your statistics are relatable. Note that the values presented should be relatable.
Think about how you will plan the data collection for your study and what two things you will be cautious of when collecting that data. Consider how you will explain to your government representative why it is necessary to collect this data and why time and money should be allocated to you to collect it
Chalabi, M. (2017, February). 3 ways to spot a bad statistic [Video]. TED Conferences. https://www.ted.com/talks/mona_chalabi_3_ways_to_s...Note: The approximate length of this media piece is 12 minutes.
Post at least 2 paragraphs in response to the following prompts:
Describe the topic you have chosen to study and explain what kinds of data you will collect to present to your government representative.
Describe two specific recommendations you would make to address uncertainty.
Explain how you will make sure that your statistics are relatable so that it will be easy to understand for a diverse group of people.
Explain two things you will be cautious of when collecting a data sample.
Then, explain to your government representative why it is necessary to collect this data and why the time and money should be allocated to you to collect it.
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Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test?Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions)Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.
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Week 6: Statistics
It is difficult to watch the news or read the paper without running into statistics. Numbers are used to support claims, report poll results, or sway you to purchase a product via advertising. Most of this data is taken from a sample or small subgroup of the population, which reduces the accuracy. Sampling, or taking data from a subset of the population, creates an opportunity for error, as not everyone in the population is represented. You may have heard a claim made, such as “three out of four dentists recommend White X toothpaste.” This sounds impressive until you learn that these dentists that recommend White X toothpaste are also given hundreds of free samples to share with their clients. These values should be critically examined for bias, bad data collection methods, or the presence of outliers that skew statistics.
This week, you will explore where data comes from, how to organize and summarize data, and how to use this to make decisions.
Discussion: Avoiding Bad Statistics
You may have heard the saying that ‘numbers never lie’. What could be more trustworthy than a solution to a mathematical equation? Enter statistics, an area of mathematics in which numbers can be used to mislead. This can be intentional, as is often the case in advertising campaigns. You might hear claims, such as the best weight loss program in the world will produce an average of 20 pounds of weight loss in the first month. Claims like these usually come with the footnote that "results are not typical" as outliers in data can affect an average value easily. One or two individuals who lost a great deal of weight can make the average value seem more impressive than it is. Misleading statistics can also be unintentional if the researcher does not consider all the important aspects.
For this Discussion, you will explore some critical considerations when assessing the accuracy of statistics.
To prepare for this Discussion:
Imagine you have been hired to complete a data analysis project to promote social change in an area important to you. Some possible topics include public transportation, distribution of public services, health care, public education, or another topic of interest.
View the video on ways to spot bad statistics and reflect on several aspects that Chalabi (2017) indicates are necessary to consider when assessing the accuracy of the values presented. Then, consider how these aspects apply to the topic you selected.
Think about what kinds of data you would collect to present in a memo to your congress person or government representative, regarding the social change you are proposing for your topic, and how you plan to address uncertainty in your results.
Think about how you will make sure your statistics are relatable. Note that the values presented should be relatable.
Think about how you will plan the data collection for your study and what two things you will be cautious of when collecting that data. Consider how you will explain to your government representative why it is necessary to collect this data and why time and money should be allocated to you to collect it
Chalabi, M. (2017, February). 3 ways to spot a bad statistic [Video]. TED Conferences. https://www.ted.com/talks/mona_chalabi_3_ways_to_s...Note: The approximate length of this media piece is 12 minutes.
Post at least 2 paragraphs in response to the following prompts:
Describe the topic you have chosen to study and explain what kinds of data you will collect to present to your government representative.
Describe two specific recommendations you would make to address uncertainty.
Explain how you will make sure that your statistics are relatable so that it will be easy to understand for a diverse group of people.
Explain two things you will be cautious of when collecting a data sample.
Then, explain to your government representative why it is necessary to collect this data and why the time and money should be allocated to you to collect it.
Cuyamaca College Guinness Brewing Company Case Study Analysis
Matched Pairs: In this lab you will learn how to conduct a matched pairs T-test for a population mean using StatCrunch. We ...
Cuyamaca College Guinness Brewing Company Case Study Analysis
Matched Pairs: In this lab you will learn how to conduct a matched pairs T-test for a population mean using StatCrunch. We will work with a data set that has historical importance in the development of the T-test.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.CONTEXTGOSSET'S SEED PLOT DATAWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows.PlotRegular seedKiln-dried Seed11903200921935191531910201142496246352108218061961192572060212281444148291612154210131614431115111535We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield.PlotRegular seedKiln-dried SeedDifference1190316092942193519152031910161129942496246333521082180–7261961192536716602122-462814441482–38916121542701013161443–1271115111535–24Note that the differences were calculated: regular − kiln-dried.VARIABLESRegular seed: regular seeds that were traditionally used for plantingkiln-dried: seed that were kiln-dried before plantingDATADownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch.PROMPTState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model.But first you will need to review the dotplots for the data (opens in a new tab).
Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test?Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions)Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.
DAT 565 University of Phoenix Sales and Advertisement Expenditure Worksheet
Respond to the following in a minimum of 175 words:Models help us describe and summarize relationships between variables. ...
DAT 565 University of Phoenix Sales and Advertisement Expenditure Worksheet
Respond to the following in a minimum of 175 words:Models help us describe and summarize relationships between variables. Understanding how process variables relate to each other helps businesses predict and improve performance. For example, a marketing manager might be interested in modeling the relationship between advertisement expenditures and sales revenues.Consider the dataset below and respond to the questions that follow:Advertisement ($'000) Sales ($'000)1068 44891026 5611767 3290885 41131156 48831146 5425892 4414938 5506769 3346677 36731184 65421009 5088Construct a scatter plot with this data.Do you observe a relationship between both variables?Use Excel to fit a linear regression line to the data. What is the fitted regression model? What is the slope? What does the slope tell us?Is the slope significant?What is the intercept? Is it meaningful?What is the value of the regression coefficient,r? What is the value of the coefficient of determination, r^2? What does r^2 tell us?Use the model to predict sales and the business spends $950,000 in advertisement. Does the model underestimate or overestimates ales?
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