Were people who contributed less than the mean of the group in any round punished more than those who contributed more than the mean? In other words, was there a norm for contributions (the mean) which was such that if you contributed less you were punished?

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Punishment

Write a report that answers the questions below. You will be judged on how well you present your arguments and the strategy you use to answer the questions.

1) In the experiment there were two groups of 5. Was there learning over the 10 rounds of the experiment?

2) Were the contributions higher in the treatment with punishment as compared to those without punishment in the first and last five rounds (I.e., compare rounds 1-10 with and without punishment and then rounds 11-20 with and without punishment)?

3) Were people who contributed less than the mean of the group in any round punished more than those who contributed more than the mean? In other words, was there a norm for contributions (the mean) which was such that if you contributed less you were punished?

4) What was the reaction of people who were punished? I.e., in the round following a punishment did people increase or decrease their contribution?

5) Classify people into two groups: Punishers and non-punishers. (Use your own classification. ) Were the payoffs of those who you classified as punishers greater or smaller than those who were not classified that way taking into account their cost of punishment?

Were people who contributed less than the mean of the group in any round punished more than those who contributed more than the mean? In other words, was there a norm for contributions (the mean) which was such that if you contributed less you were punished?

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DISCUSSION ESSAY

Write a report that answers the questions below. You will be judged on how well you present your arguments and the strategy you use to answer the questions.

1) In the experiment there were two groups of 5. Was there learning over the 10 rounds of the experiment?

2) Were the contributions higher in the treatment with punishment as compared to those without punishment in the first and last five rounds (I.e., compare rounds 1-10 with and without punishment and then rounds 11-20 with and without punishment)?

3) Were people who contributed less than the mean of the group in any round punished more than those who contributed more than the mean? In other words, was there a norm for contributions (the mean) which was such that if you contributed less you were punished?

4) What was the reaction of people who were punished? I.e., in the round following a punishment did people increase or decrease their contribution?

5) Classify people into two groups: Punishers and non-punishers. (Use your own classification. ) Were the payoffs of those who you classified as punishers greater or smaller than those who were not classified that way taking into account their cost of punishment?

Following the Box-Jenkins methodology, identify an appropriate ARIMA(p,d,q) model for your company’s return. Provide a clear explanation of the identification, estimation, and diagnostic stages of the modelling process.

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Box-Jenkins methodology

Following the Box-Jenkins methodology, identify an appropriate ARIMA(p,d,q) model for your company’s return. Provide a clear explanation of the identification, estimation, and diagnostic stages of the modelling process.

Company data is attached.

  • https://www.studypool.com/questions/download?id=2807745&path=uploads/questions/2859972/20230413194807company_return_data.xlsx&fileDownloadName=attachment_1

When to use a random number generator? What are the differences in sampling with and without replacement and why does that matter?

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Random Number Generators (PLG1)

First, research random number generators. Then, respond to the following using the following Random Number Generator Template assignment template:

  • When to use a random number generator?
  • What are the differences in sampling with and without replacement and why does that matter?
  • Provide a URL link or source (If source use APA documentation)
  • Screenshot (at least 10 numbers created by Random Number Generator)
  • Reference List (at least two using current APA format)

Explain 3a in plain language, like you’d explain it to Grandma. How would you explain the effect of committing to actually call a loved one on self-esteem?

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SPSS Assignment #3

What you will need:

  • sav
  • sav
  • Answer-Sheet document, saved as Last_First_SPSS3
    • Top-left corner: your name, uta email address, [due date], SPSS #3
  • The PSYC 2300 manual helps a lot…
    • … Otherwise, be prepared to Google “how to ____ in SPSS” several times.

 

HELPFUL TIPS:

  • BE VERY CAREFUL TO PRECISELY FOLLOW THE APA-FORMATTING DEMONSTRATED IN THE PPT SLIDES AND THE 2300 SPSS MANUAL! Points will be deducted for seemingly minor issues such as correct usage of italics, sp a cing, and what specific details are reported for each analysis. Some examples: p should always be written in lowercase italics… put one space on each side of an + or < sign: p = .002 instead of p=.002….
  • If you don’t understand what the words you’re typing mean, you are probably typing something that doesn’t make sense, and points will be deducted. Read what you wrote. Make sure it makes sense. Get feedback during class or during stat-tutor club.
  • For this entire assignment, regardless of the research hypothesis, report the two-sided/two-tailed p – the one they give you by default… The two-tailed p is more conservative – less prone to type-1 error – so nobody will ever complain if you report a two-tailed p for a one-tailed test, even if a one-tailed test is technically correct, given the research hypothesis.

 

 

 

 

  1. In the dataset sav, go to Variable View… expand the Labels column as wide as it will go. This column shows you exactly what participants were asked in this survey.

    Based on reading the variable labels in variable view…

… What do you think was the purpose of this survey?

… Is there a certain difference you think Dr. Adams was hoping to find between selfesteem_t1 (the first question) and selfesteem_t2 (the last question)?

In as few words as possible, in your Answer-Sheet Document, explain your answers to these two questions.

  1. To test whether there was a difference between selfesteem_t1 and selfesteem_t2, run a repeated measures t-test (see manual pp. 36-38 + repeated-measures lecture slides).
    1. Screenshot/Paste the output into your Answer-Sheet Document
    2. summarize the result in APA format.
    3. Forget about APA format etc… Based on the result of this test, what would you conclude about the effect of [_? 🤔 ?_]  on self-esteem? In plain language – like you’d explain it to Grandma – what general conclusion would you draw from this study? Use as few words as possible to make your point. It’s possible to earn full points on 2c with a single sentence!

 

 

  1. Adams wonders if the overall boost to participants’ self-esteem in this survey was dependent on whether they committed to calling a loved one immediately after class on Monday. To explore this possibility, “split the file” by willyoucall (manual p. 19). NOTE: When you turn on “split the file by willyoucall,” nothing will happen immediately. Now that the file is split, however, you will receive two separate chunks of output for any analyses you run: one chunk of output for participants who responded “okay, yes, I will call…” and another chunk for those who responded “nah…”
    1. With split-file by willyoucall turned on, run the same exact analysis as in #2. Paste the two different chunks of output into your document, and explain the results in APA format.
      HINT: Your write-up should take this form:
      Among participants who did not commit to calling a loved one after class, __[t-test results in APA format]
      By contrast, among participants who committed to calling a loved one after class, __[t-test results in APA format]__      .”
    2. Explain 3a in plain language, like you’d explain it to Grandma. How would you explain the effect of committing to actually call a loved one on self-esteem?

CLOSE SPSS3_self-esteem.sav

 

OPEN UAlabama_dataset_2017.sav

 

 

  1. Run a bivariate correlation analysis on the variables happiness_1 and HoursTV_1
    (see manual p. 71 + Correlation lecture slides). ***

    ***HINT: Within the correlation dialog box, if you right-click on the list of variables on the left, you can choose Display Variable Names and Sort Alphabetically – this makes it much easier to find specific variables (e.g., happiness_1).

    Paste the output into your AS Document and report your results in APA format.

  2. Choose two other variables for which you would hypothesize a significant correlation. Run a bivariate correlation analysis, screenshot/paste the output, and report the results in APA format. NOTE: for a correlation analysis, you should NOT use categorical variables; use variables with a range of numerical values.
  3. Choose five other variables that you think might be correlated with each other. Add them all to a bivariate correlation analysis (only these new 5; not the prior two). Paste the correlation matrix into your document and report the results of three of these correlations in APA format. For any significant correlations, also provide a simple, one-sentence explanation of the relationship: In other words Variable1 increases/decreases, Variable 2 tends to increase/decrease.

 

 

Save your datasets. Save your AS Document. Save your AS Document as a PDF. Email all of the files to yourself. Submit your PDF – Lastname_Firstname_SPSS3.pdf – on Canvas.

What is the article or ad trying to say? What statistical data are misrepresented or exaggerated? What are the undesirable consequences to the consumer of this information?

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Statistics in the Media Discussion

We hear and see statistics in the news all the time. Examples include statistics about crime rates, children killed by handguns, pool drownings, people struck by lightning, and causes of car accidents. Should we take them at face value? Is it true just because it is in the news?

Another example from the world of advertising:

According to the Center for Disease Control (CDC), about 38 million Americans still smoke. Cigarette smoking was especially high among males between 25-64 years old. Since 1964, a warning on the side of each pack of cigarettes has informed the public that smoking is bad for human health and may cause cancer or contribute to other diseases. Still, 480,000 Americans will die of smoking this year (CDC 2020). This figure is shockingly high, exceeding the total number of wartime deaths suffered by 405,399 U.S. military in WW II (Green, 2017). For each smoker who dies, 30 more continue to live with a smoke-related disease. Yet, 15.5% of Americans 18 and younger pick up the habit. The CDC estimates that cigarette and smokeless tobacco industries spent over $9 billion on advertising and promotional expenses in the US in 2018 (CDC 2018).

How do company/industry funded studies get us to do things most of us agree are bad for our health? This four minute video on the effects of cholesterol Links to an external site. is a great example of why we replicate studies and why “who funded the study” is so important

Sources:

Locate an article or advertisement that provides statistics in support of its message. Attach the article or advertisement link to your initial post.

  • What is the article or ad trying to say?
  • What statistical data are misrepresented or exaggerated?
  • What are the undesirable consequences to the consumer of this information?

Tip: Copy and paste the bulleted questions into your initial post.

Use current APA formatting to cite/reference your source(s).

Make your initial post by the end of today of the module week. Remember to include a summary of your research.

What should we conclude about the analysts claim? Solve the test statistic approach. Use the following statistics to solve the problem. n = 15 = $1831.067 S = $506.59

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Statistics questions

Top of Form

Apply the applicable rule before solving any problem.  Show the formula, and graph where applicable.

 

1a) Sx  is a known estimate: True or False

 

1b) Population mean is a known estimate:  True or False

 

1c) The objective of a confidence interval is not to bracket the fixed population mean:  True or False

 

1d) T-test discusses the deviation of a random variable  from its mean measured in standard deviation of the sample mean units:  True or False

 

1e) T-test is used to test a hypothesis about the population mean: True or False

 

 

Standard Normal Probability Distribution

 

2) Find the probability that the random value of Z is between +.65 and +.2.33.

 

 

 

T distribution is symmetric and t table gives values of t such that the probability of the larger t is equal to a given probability.

 

3a) P(t > to) = 0.10 given a sample size of 13.

Find to

 

3b) P(-to  > t > + to) = 0.05 given a sample size of 9.

Find to

 

3c) P(t <  2.1098) = ? given a sample size of 18.

Find the associated probability.

 

Consider the probability that a random interval x ± (t.05)S will contain the fixed μ (population mean) is .95  That is:

 

P( – t.05S ≤  μ ≤   + t.05S) = .95.

 

4) Construct a Confidence Interval given the following:

Sample size = 10,  = 131, S2 = 971.11.

 

T test:

5) If a real estate market is strong, there will be a close relationship between the asking price for homes and the selling price.  Suppose that one analyst believes that the mean difference between asking price and selling price for homes in a particular market area is less than $2000.  To test this using an alpha level equal to .05, random sample of n=15 homes that have sold recently was selected.  The difference between asking price and selling price data from the sample is in the following:

 

$2053 $1693 $1854 $1747 $869
$1396 $2473 $1931 $2303 $1502
$1038 $2755 $2084 $1664 $2104

 

What should we conclude about the analysts claim?  Solve the test statistic approach.  Use the following statistics to solve the problem.

n = 15     = $1831.067         S = $506.59

 

 

 

Create a simple distribution graph (histogram) where we will explore the age of women after giving birth to their first child. Remember that a histogram consists of parallel vertical bars that show the frequency distribution of a quantitative variable in the graph.

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Summarizing Data Collected in a Defined Population Sample (Biostatistics)

Critical Thinking Assignment

This week we are learning about ordinal/categorical, continuous, and dichotomous variables. Using the Gestation Demographics SEU dataset that is located in the tabs at the bottom of the Framingham dataset provided, perform the following problems using R Studio or Excel.

  • Create a simple distribution graph (histogram) where we will explore the age of women after giving birth to their first child. Remember that a histogram consists of parallel vertical bars that show the frequency distribution of a quantitative variable in the graph. See the example in Introductory Statistics with R on pages 71-7 or pages 123-124 in EXCEL statistics A quick guide. The area of each bar is equal to the frequency of items found in each class.
  • Determine the mean age of the women in the Gestation Demographics SEU dataset.
  • We will be testing the hypothesis that the mean age (μ = μ0) for women is 37 years in the Gestation Demographics SEU dataset. The topic of hypothesis testing was introduced in HCM505. If you need a review see Chapter 7 of our text.

H0 The mean age of women giving birth is 37 years old. (Null Hypothesis)
H1 The mean age of women giving birth is not 37 years old. (Alternative Hypothesis)

Ensure to submit the following requirements for the assignment:

  • Present your findings in a Word document, by copying and pasting the histogram into the document.
  • After your analysis state whether you accept or reject the null hypothesis and your reasoning why.
  • Always use a title page, an introduction, a discussion where you interpret the meaning of the histogram, and a conclusion should be included.
  • Your submission should be 3 pages to discuss and display your findings.
  • Provide support for your statements with in-text citations from a minimum of three scholarly, peer-reviewed articles. One of these sources may be from the class readings, textbook, or lectures, but the others must be external. The Saudi Digital Library is a good place to find these sources and should be your primary resource for conducting research.
  • Follow APA 7th edition and Saudi Electronic University writing standards.

Which team won the higher proportion of gold medals? Work out how many gold medals each team won. Which team won the higher number of gold medals?

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Work out the amount of gold medals both teams won

The medals won by two teams in a competition are shown below.
a) Which team won the higher proportion of gold medals?
b) Work out how many gold medals each team won.
c) Which team won the higher number of gold medals?

Compute the value of Altman’s Z-score for Delta Air Lines for each year from 2000 to 2004.

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HW-Financial Ratios

Delta Air Lines, Inc., is one of the largest airlines in the United States. It has operated on the verge of bankruptcy for several years. Table below presents selected financial data for Delta Air Lines for each of the five years ending December 31, 2000, to December 31, 2004. Delta Air Lines filed for bankruptcy on September 14, 2005.

Financial Data for Delta Air Lines, Inc. (amounts in millions, except per-share amounts)

1) Compute the value of Altman’s Z-score for Delta Air Lines for each year from 2000 to 2004.