Week 1: Week 1 – Class Discussion
Apply statistical concepts to your daily life.
Does regular exercise reduce the risk of a heart attack? Here are two ways to study this question.
Example Study 1: A researcher finds 2,000 men over 40 who exercise regularly and have not had heart attacks. She matches each with a similar man who does not exercise regularly, and she follows both groups for five years.
Example Study 2: Another researcher finds 4,000 men over 40 who have not had heart attacks and are willing to participate in a study. She assigns 2,000 of them into a regular program of supervised exercise. The other 2,000 continued their usual habits. The researcher follows both groups for five years.
Review the example studies above and answer the following questions in your main post:
After reviewing the examples above, create your own study that will determine if regular exercise reduces the risk of a heart attack.
Is your study more similar to example study one or example study two? Why?
Given that example study one is an observational study and example study two is an experiment, is your study an observational study or an experimental study? Explain.
Why does the second way of studying the question (the experiment), give more useful information about whether exercise reduces the risk of heart attacks?
What population do you think the researcher wants information about in example study two? What was the sample in this case? Does your study examine the same sample? Explain.
Week 2: Week Two – Class Discussion
Interpret the process of collecting unbiased data for observational studies and experiments.
Ann Landers (1918 2002) was a syndicated advice columnist whose daily column was published in over 1,200 newspapers in the United States and Canada. One of her columns from 1976 turned into survey on parenthood.
It sounded like a simple survey easy to understand, easy to execute, and relatively inexpensive with the survey costs limited to the recording of the responses. There were many responses, at least 10,000, which made the statistical efficiency excellent. The survey of 1975-76 examined the issue of whether or not parents would have children if they were able to live their lives over again. To her surprise, 70% of the respondents said No.
Youve been asked to investigate this statistical result. After reading Section 1.5, you should discuss the following in your main post:
What is your initial reaction to this statistical result?
Research and provide an example survey that produced statistical results that were unexpected. (Remember to list all of your resources)
Critique the study you researched, in part b, based on what you learned in Chapter 1. In particular, discuss the sampling design used in this study and any issues of bias.
Why does the second way of studying the question (the experiment), give more useful information about whether exercise reduces the risk of heart attacks?
Using your critique in question c, is there a better way to do this study? If so, what would you specifically change in your approach?
Week 3: Week Three – Class Discussion
Analyze different ways to organize and summarize data.
The following figure comes from a study of lightning storms in Colorado. It shows the distribution of the hour of the day of lightning strikes during the entire 2013 year.
.gif” alt=”Lightning strike”>.jpg”>
Answer the following questions for your main post:
What are the 3 times of the day that you are most likely to encounter lightning strikes?
Describe the shape, center, and spread of this graph.
Are there any outliers?
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d. How many lightning strikes occur after the time next to the first letter of your first name? (EX. Jane: J-9AM, thus, how many lightning strikes occur after 9am?)
e. How many lightning strikes occur between the times located next to the first letter of your first name and first letter of your last name? (Ex. Jane Smith: J-9AM, S-6PM, thus, how many lightning strikes occur between 9AM and 6 PM?)
f. Congratulations! You were just hired by a local weather station to help them with their statistics since they found you are taking this statistics course. Give a brief 2 to 3 sentence summary of what this graph is saying and how it might be helpful to this weather station. Remember they hired you because they needed your help on this so make sure you give them a summary that is useful and insightful!
Week 4: Week Four – Class Discussion
Analyze different ways to organize and summarize data.
Apply statistical methods for organizing and summarizing data both graphically and numerically.
The cover of the from December 7, 2000 is shown below:
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Answer the following questions for your main post:
Identify the two variables being graphed. What types of variables are they? What is the level of measurement for each of the variables?
What method would you use to collect data for this graph? Why would you use this particular method?
What type of graph is displayed? If you could use any type of graph other than the one shown, what type of graph would you use? Why?
After looking at this graph, would you want to attend Cornell University? Why? What message does this graph convey to you? How might this graph be misleading?
Describe at least three things that are wrong with the graph.
Find an example of a misleading graph online. Post a link to the graph, and briefly discuss the qualities of the graph that made it misleading.
Week 5: Week Five – Class Discussion
Recognize how probability applies to your daily life.
Suppose you are in the market to purchase a used car. To make an informed decision regarding your purchase, you would like to collect as much information as possible. Among the information you might consider are the typical price of the car, the typical number of miles the car should have, its crash test results, insurance costs, and expected repair costs.
Respond to all of the following prompts:
Make a list of at least two cars that you would consider purchasing. To be fair, the cars should be in the same class (such as compact, midsize, and so on) and made in the same year.
Collect information regarding the two cars in your list by ?nding at least eight cars of each type that are for sale. Obtain information such as the asking price and the number of miles the car has. Sources of data include your local newspaper, classi?ed ads, and car websites (such as.cars.com/”>www.cars.com). Compute summary statistics for asking price, number of miles, and other variables of interest. Summary statistics should include the mean, standard deviation, median, and range. In your main post, present your data, plus the summary statistics for each car.
Go to the Insurance Institute for Highway Safety website (.iihs.org/”>www.iihs.org). Select the Vehicle Ratings link. Choose the make and model for each car you are considering. Obtain information regarding crash testing for each car under consideration. Compare cars in the same class. How does each car compare? Is one car you are considering substantially safer than the other? What about repair costs? Compute summary statistics for crash tests and repair costs. Remember summary statistics should include the mean, standard deviation, median, and range.
Your best friend is looking into buying a car and happens to be debating between the exact makes and models you have chosen. Which car would you advise your friend to buy? Support your opinion by explaining which has the highest asking price; which has the highest average repair cost; and which has the most consistent asking price (hint: use the standard deviation to answer this).
Week 6: Week Six – Class Discussion
Compute probabilities using the Addition Rule, Multiplication Rule, and Counting Techniques.
A study was conducted on high school students in 2008. The research aimed to study the effect of assertiveness (confidence) training on educational anxiety. Educational anxiety can have a large impact on students during their teen years. It threatens students psychological health and affects their efficiency, aptitude, personality formation, and social identity. Assertiveness training is a structured intervention process that is used for social relationship improvement, anxiety disorder therapy, and phobias in children, teenagers, and adults. It seems that low assertiveness and high anxiety in students creates educational dysfunction, reduces the ability to learn, and produces a decrease in aptitude.
Anxiety is measured with a 30 question questionnaire using yes/no answers. The maximum score is 30, minimum is 0, and high anxiety is anything greater than 21. Assertiveness is also measured by a questionnaire with a minimum score of 30 (low assertiveness) to a maximum of 180 (high assertiveness). The following is a summary of their findings:
.gif” alt=”Anxiety”>.gif” alt=”Anxiety”>.jpg”>
Refer to the following table and answer the following questions for your main post:
Did boys or girls have greater educational anxiety? What cultural variables may lead to this result?
Did boys or girls have greater assertiveness? What cultural variables may lead to this result?
Would knowing this was a sample of 30 students or 1,000 students change how you view this data? Why? How does the sample size affect the data?
What is the standard deviation telling you about anxiety and assertiveness between boys and girls? Which group is more consistent? Which group is less consistent?
Do you feel the differences in values between boys and girls are enough to say there is a real statistical difference between them? Why or why not?
Week 7: Week Seven – Class Discussion
Interpret probability models for random variables.
It is well-documented that parents actively smoking during pregnancy is associated with lower-birth-weight babies. Researchers Fernando D. Martinez and associates wanted to determine if there is a relationship between paternal smoking habits and birth weight. The researchers administered a questionnaire to each parent of newborn infants. One question asked whether the individual smoked regularly. Because the survey was administered within 15 days of birth, it was assumed that any regular smokers were also regular smokers during pregnancy. Birth weights for the babies (in grams) of nonsmoking mothers were obtained and divided into two groups, nonsmoking fathers and smoking fathers. The given data below represents the data collected by the researchers. The researchers concluded that the birth weight of babies whose father smoked was less than the birth weight of babies whose father did not smoke.
Answer the following questions for your main post:
Nonsmokers
4194
3522
3454
3062
3771
3783
3544
3746
4019
4248
3719
3668
3128
3290
3423
3471
4354
3544
3994
2976
4067
3732
3823
3302
3436
3976
3263
Smokers
3998
3455
3066
3150
2986
2918
4216
3502
3457
2860
3282
2746
3686
2851
3145
3807
3548
4104
3963
3892
2768
3769
3509
3629
4131
3129
4263
Is this an observational study or a designed experiment? Why?
What is the explanatory variable? What is the response variable?
Can you think of any lurking variables that may affect the results of the study?
Go to.xuru.org/st/DS.asp”>http://www.xuru.org/st/DS.asp and find the summary statistics for both non-smokers and smokers (mean, median, standard deviation, quartiles.) Compute each group separately. Report your findings. Note: Copy the data from the tables and place in the large box on the page and separate each item by a comma.
Why is the sample standard different from the population standard deviation? Which should you use in this study, and why?
Using your results, write up a practical summary of what you are seeing in this data. Do you agree with the researchers conclusions based on your analysis?