PROJECT 3: Exploring Local and Global Values GUIDEBOOK For this project, you will be asked to do a little research and perform two types of hypothesis tests using data from the Global Values Survey. First, you will perform a single-sample hypothesis test, where you will compare data from your class to the global population on a single variable. The second test, an independent-samples hypothesis test, will have you explore how two different group means compare on a single variable. You will also be asked to evaluate the work of your peers. This project embodies learning goals and objectives 2, 5, 6, and 7 as listed in the syllabus. TABLE OF CONTENTS SECTION A: PROJECT INSTRUCTIONS ............................................................................................................2 SECTION B: CODEBOOK.....................................................................................................................................5 SECTION C: ANALYSIS INSTRUCTIONS ........................................................................................................9 SECTION D: RUBRIC .........................................................................................................................................13 SECTION E: EXAMPLE PROJECT ...................................................................................................................15 REQUIRED MATERIALS  A word processing program to type up your final REPORT (e.g., Microsoft Word)  The data analysis program SPSS  The data FILE (.sav file located on Canvas) containing all of the variables and scores from the sample  The CODEBOOK (SECTION B) containing a list of the variables and values you may use  ANALYSIS INSTRUCTIONS (SECTION C) explain how to use SPSS  Your NOTES from lessons 8.1 and 8.2  The RUBRIC (SECTION D)  A project EXAMPLE (SECTION E) 1 SECTION A: PROJECT INSTRUCTIONS Description. For this project, you will be asked to do a little research and perform two types of hypothesis tests using data from the Global Values Survey. First, you will perform a single-sample hypothesis test, where you will compare data from your class to the global population on a single variable. The second test, an independent-samples hypothesis test, will have you explore how two different group means compare on a single variable. You will also be asked to evaluate the work of your peers. Organization. Your final report will be organized by test. The following is how your report will be organized:    PART A  TEST ONE: SINGLE-SAMPLE HYPOTHESIS TEST 1. Introduction and descriptive statistics (10 points) 2. Hypothesis statement (10 points) 3. Annotated test statistics (10 points) 4. Hypothesis decision (5 points) 5. Reflection (10 points)  TEST TWO: INDEPENDENT-SAMPLES HYPOTHESIS TEST 6. Grouping variable information (10 points) 7. Hypothesis statement (10 points) 8. Annotated test statistics (10 points) 9. Hypothesis decision (5 points) 10. Reflection (10 points) PART B: PEER EVALUATION o Provide a peer evaluation for two of your classmates (10 points) PART C: OPTIONAL REVISION o You may revise your project over the course of the next week. Stepwise instructions. For information on how to perform these tests in SPSS, please refer to the Analysis instructions (SECTION C). For the rubric and an example project, please refer to SECTIONS D and E. TEST ONE: SINGLE-SAMPLE HYPOTHESIS TEST Please select ONE “Global Values” variable measured at the interval-ratio level using the codebook (SECTION B). For this project, you may consider the variables ‘q4a’ through ‘q66g’ as interval-ratio because they are measured on a numeric scale ranging from ‘1-4’ or ‘0-10.’ 1. Introduction and descriptive statistics. Describe the variable are you exploring. Use SPSS to generate the following statistics about your variable but treat them as population parameters (hint – you can refer back to instructions from project 2 on how to obtain descriptive statistics using SPSS):  Population size (N=___)  mean, median, mode, standard deviation,  standard error,  the minimum/maximum values, and the range. Then, in a full paragraph, critically reflect on these parameters. What does prior research say about this relationship you’re measuring (USE ONE EXTERNAL RESOURCE)? What is the best measure of central tendency and what does that value mean? What is the standard error? Is there any skew? Why/why not? Keep in mind that you may be reporting on a variable measured on a scale ‘1-4’ or ‘02 10,’ so what does your obtained mean value REALLY indicate? What does this value say about your population? (i.e., who are you talking about -- the whole globe or a smaller subset of countries)? 2. Hypothesis statement. For this single-sample hypothesis test, you’re assessing how the class sample mean compares with the global population mean on your selected variable. In the codebook, I’ve recorded the mean values from the class sample (to be treated as a test value) next to each variable. Write a two-tailed null and research hypothesis using symbols AND using appropriate statistical language.  HINT: Page 181-183 in your book covers hypothesis construction for single samples. 3. Annotated test statistics. Perform a one-sample hypothesis test. Report and label the following statistics. For each, include a one-sentence interpretation of what that actual numeric value means.  mean difference  the degrees of freedom  the obtained t-statistic  the t-critical  the P value 4. Hypothesis decision. Using appropriate statistical language, formally state your decision regarding your hypothesis in one sentence. Assume your α (alpha) is set at a 0.05 level. 5. Reflection. In a full paragraph, provide an informed reflection. Be sure to pull in your previous research, information about most of the parameters/statistics you’ve reported, your data, and the samples and populations you’re testing, critically reflect on your analysis. You should consider the following questions: What does a previous study related to this information tell us? Why do you think you obtained this result? What does it mean? Is your variable measured in the best way possible? What do the results of your test indicate? What do your findings say about the sample? Is it generalizable to the world? A type of population? Are your findings consistent with other findings? (HINT: I list which countries we may compare our data in the codebook?) What other variables in the codebook might these variables be related to? TEST TWO: INDEPENDENT-SAMPLES HYPOTHESIS TEST For PART TWO, you will need to select a sorting variable and use it to test mean differences on your outcome variable used in part one. This sorting variable should be DICHTOMOUS (I have indicated such in the codebook). 6. Grouping variable information. The goal of independent samples t-tests are to assess how two different groups vary on one variable. Here, I'd like you to explore how two groups vary with respect to your outcome variable. Please report the initial mean differences, report the mean, standard deviation, and standard error of the mean of your chosen variable using your grouping/sorting variable. Then, in a full paragraph, critically reflect on these parameters. Questions to consider are: What does prior research say about this relationship you’re measuring (USE ONE EXTERNAL RESOURCE)? What is the best measure of central tendency and what does that value mean? What is the standard error? Is there any skew? Why/why not? Keep in mind that you may be reporting on a variable measured on a scale ‘1-4’ or ‘0-10,’ so what does your obtained mean value REALLY indicate? What does this value say about your population? (i.e., who are you talking about -- the whole globe or a smaller subset of countries)? 7. Hypothesis statement. The goal of an independent samples t-test is to assess how two different groups (e.g., people sorted by gender, citizenship, marital status, age, etc.) vary on one outcome variable. Write a one-tailed null and research hypothesis using symbols AND using appropriate statistical language. If you need to, please include a narration/explanation of the hypothesis. 3  HINT: Page 195 in your book covers hypothesis construction for independent-samples tests. 8. Annotated test statistics. Perform an independent-samples hypothesis test. Report and label the following statistics. For each, include a one-sentence interpretation of what that value means. Please assume equal variances.  mean difference  standard error of the difference  the degrees of freedom  the obtained t-statistic  the t-critical  the P value 9. Hypothesis decision. Using appropriate statistical language, state your decision regarding your hypothesis in one sentence. Assume your α (alpha) is set at a 0.05 level. 10. Reflection. In a full paragraph, provide an informed reflection. Using one external resource, information about the statistics you performed, your data, and the samples and populations you’re testing, critically reflect on your analysis. You should consider the following questions: What does a previous study related to this information tell us? Why do you think you obtained this result? What does it mean? Is your variable measured in the best way possible? What do the results of your test indicate? What do your findings say about the sample? Is it generalizable to the world? A type of population? Are your findings consistent with other findings? (HINT: I list which countries we may compare our data in the codebook?) What other variables in the codebook might these variables be related to? PART B: PEER EVALUATION Evaluate two other students’ projects by submitting a reply post to each by the second deadline. Your evaluations should use information you have learned from your textbook and the memos. You must provide ONE piece of feedback for two projects. For example, did they select appropriate variables? Did they construct their hypothesis correctly? Is their causal logic sound? Do they provide an adequate reflection? If you evaluated a FLAWLESS project, you must describe why they are, indeed, flawless.     You are responsible for posting brief evaluations for TWO of your classmates’ projects. So that each person has the benefit of two evaluations, please do not evaluate projects that already have two replies. To post your evaluations, click “reply” to the post you wish to respond. In your evaluations, you must provide quotations (for example, if you're directing your classmate to rewrite a question, include the text from their question in your response post. If your mentors and I cannot tell which response to which you have replied, you will not receive credit for this portion of the assignment. PART C: OPTIONAL REVISION By the final due date, you are welcome to read your classmates' feedback and post a REVISED version of your project to the discussion board. This is an opportunity to incorporate feedback and make any changes you see fit. Here are the rules:    Use your best judgement when evaluating student feedback -- make only changes you think are logical. You may not change your ENTIRE project (your original post and revision post must be similar). No late projects! If you did not submit a project by the initial deadline, you may not post one by the second deadline. You do not have to revise your work -- we will grade the latest posting available. 4 SECTION B: CODEBOOK A codebook will contain all possible variables in a given data set (full text questions listed below the table). Typically, codebooks will contain descriptive measures, but since your job is to report those, I’ve left them out of this codebook. This data contains measures from several different samples as follows (the last column, “Sampled Countries,” lets you know from which sample each variable is derived):    United States. Data drawn from US-occupants only. Select Countries. Data drawn from the following countries: ARGENTINA, BANGLADESH, BRAZIL, CHILE, CHINA, COLOMBIA, EGYPT, EL SALVADOR, GHANA, INDIA, INDONESIA, JORDAN, KENYA, LEBANON, MALAYSIA, MEXICO, NICARAGUA, NIGERIA, PAKISTAN, PALESTINIAN TERRITORIES, PERU, PHILIPPINES, POLAND, RUSSIA, SENEGAL, SOUTH AFRICA, TANZANIA, THAILAND, TUNISIA, TURKEY, UGANDA, UKRAINE, VENEZUELA, and VIETNAM. All Countries. Data drawn from the following countries: ARGENTINA, BANGLADESH, BRAZIL, CHILE, CHINA, COLUMBIA, EGYPT, EL SALVADOR, FRANCE, GERMANY, GHANA, GREECE, INDIA, INDONESIA, ISRAEL, ITALY, JAPAN, JORDAN, KENYA, LEBANON, MALAYSIA, MEXICO, NICARAGUA, NIGERIA, PAKISTAN, PALESTINIAN TERRITORIES, PERU, PHILIPPINES, POLAND, RUSSIA, SENEGAL, SOUTH AFRICA, SOUTH KOREA, SPAIN, TANZANIA, THAILAND, TUNISIA, TURKEY, UGANDA, UKRAINE, UNITED KINGDOM, UNITED STATES, VENEZUELA, AND VIETNAM. Socio-Demographic Data (GROUPING/SORTING Variables) Code GENDER PARENT Under40 STATSvsWORLD USARESIDENTS STATSandUSA G8Residents Variable Description Response Categories Separates sample by women and men. Separates sample by people who have children and those who do not. Separates sample by major age group. Separates sample by class and other countries surveyed Separates sample by USA residents (including class) and other countries surveyed Separates sample by stats class and USA Separates sample by those who are in G8 and non-members. Household Resources q148_a Television q148_b Refrigerator q148_c Washing Machine q148_d Microwave Oven q148_e Computer q148_f Car q148_g Bicycle q148_h Motorcycle/Scooter q68 Cell Phone 1=Man; 2=Woman n/a Sampled countries All countries 1=Has at least one biological child; 0=has no biological children 1=Under 40; 2=40 and older 1=STA2122; 2=Rest of World 1=USA; 2=Rest of World n/a All countries n/a All countries n/a All countries n/a All countries 1=STA2122; 2=USA n/a United States 1=US, UK, France, n/a Germany, Italy, Japan, and Russia; 2=Rest of World All countries 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes 1=no; 2=yes n/a n/a n/a n/a n/a n/a n/a n/a n/a Mean All countries All countries All countries All countries All countries All countries All countries All countries All countries 5 Global Values Data Codes Variable Name Satisfaction with… q4a Standard of living q4b Family life q4c Health q4d Social Life q4e Present job q4f Religious life q4g Safety of Neighborhood q4h Quality of Schools Important aspects of life q14a Job q14b Travel q14c Internet q14d Cell Phone q14e Free time q14f Help others q14g Own home q14h Good education q14i Own car q14j Money in old age q14k Good health q14l Safe from crime Country’s Problems q21a Crime q21b Corrupt political leaders q21c Poor quality schools q21e Air pollution q21f Water pollution q21g Safety of food q21h Health care q21i Traffic q21j Electricity shortages How important are each to get ahead q66a Good education q66b Work hard q66c Know the right people q66d Give bribes q66e Be male q66f Belong to wealthy family q66g Be lucky Categories Mean from class sample (n=134) “Test Value” Sampled countries Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 7.78 7.81 7.21 6.66 6.23 7.13 7.60 6.99 Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 8.96 8.08 8.10 7.91 8.78 8.48 8.00 9.41 8.26 8.88 9.51 9.13 Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries 4 categories 4 categories 4 categories 4 categories 4 categories 4 categories 4 categories 4 categories 4 categories 1.66 1.44 1.57 1.64 1.56 1.93 1.55 2.42 2.58 Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Select Countries Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 Range 0 to 10 9.10 9.32 7.91 2.51 4.12 5.11 4.66 All countries All countries All countries All countries All countries All countries All countries 6 ---STA2122 Global Survey QUESTIONS--Q148 (a to i) And in your household, do you have any of the following? Count only those that are in working order.          television refrigerator washing machine microwave oven computer car bicycle motorcycle or scooter radio Q68 Do you own a cell phone? (code q68)   Yes No Q4 (a to h) On a scale of 0 to 10 how satisfied are you with each of the following, where 0 means you are very dissatisfied and 10 means you are very satisfied? (code q4) ______ Your present standard of living ______ Your family life ______ Your health ______ Your social life ______ Your present job ______ Your religious life ______ The safety of your neighborhood ______ The quality of schools where you live Q13 Please tell me whether you completely agree, mostly agree, mostly disagree or completely disagree with the following statements: a. Most people are better off in a free market economy, even though some people are rich and some are poor b. Success in life is pretty much determined by forces outside our control. (code q13)     Completely agree Mostly agree Mostly disagree Completely disagree Q14 (a to l) Some people say the following things are important to them. On a scale of 0 to 10, how important is each thing to you personally, where 0 means not important at all and 10 means very important. (code q14) ______ To have a fulfilling job ______ To be able to travel ______ To have internet access ______ To own a cell phone ______ To have free time for yourself ______ To help other people who are in need ______ To own your own home ______ To have a good education for you children 7 ______ To own your own car ______ To have money for old age ______ To have good health ______ To be safe from crime Q21 (a to j) Now I am going to read you a list of things that may be problems in our country. As I read each one, please tell me if you think it is a very big problem, a moderately big problem, a small problem or not a problem at all. (code q21) Very Big Problem Moderately Big Problem Small Problem Not a problem at all crime     corrupt political leaders     poor quality schools     air pollution     water pollution     safety of food     health care     traffic     electricity shortages     Q66 (a to g) On a scale of 0 to 10, in your opinion, how important is it ___________ to get ahead in life. The number 0 means not important at all and 10 means very important? (q66) ______ TO HAVE A GOOD EDUCATION ______ TO WORK HARD ______ TO KNOW THE RIGHT PEOPLE ______ TO GIVE BRIBES ______ TO BE A MALE ______ TO BELONG TO A WEALTHY FAMILY ______ TO BE LUCKY 8 SECTION C: ANALYSIS INSTRUCTIONS One Sample T-Test  Once your data are open, click “Analyze”, then “Compare Means”, and finally “One-Sample T Test…” to open the menu to conduct a one sample t-test. Remember that you will be conducting a two-tailed one sample t-test, and I have set your alpha level at (α=0.05).  Next, select your test variable. I will test the variable H2EE8, which is a variable from Wave II of the National Longitudinal Study of Adolescent Health that reports the dollar amount of a respondent’s weekly allowance.  For my purposes, I am going to set the Test Value as 0 dollars. We are working with sample data in this case. I chose $0 since I did not have a weekly allowance, and I want to see how different the respondents’ weekly allowance was from mine. IF YOU HAVE ANOTHER MEAN VALUE TO USE, YOU NEED TO IMPUTE IT HERE ALSO (for example, you might want to test the mean value from you class data). 9   Click “OK” to have SPSS run the t-test. Go to the “Output” window, if it doesn’t open automatically. Your output will look something like this:  So what does all of this mean? Let’s go over it one by one. I have enclosed a red box around everything you will need to know for Project 3 in the following picture. o The first box shows “One-Sample Statistics”. These are similar to what we would get if we had SPSS report the frequencies with the options of mean, standard deviation, and standard error of the mean selected. These are the same as discussed in your book and in the memos. o The second box shows the “One-Sample Test”, which is our t-test. o The obtained t is labeled as simply t and is 45.309. This is our test statistic. o The degrees of freedom are labeled as df. We have 4778 degrees of freedom. o The P-value is labeled as Sig. (2-tailed). Our p-value is 0.000. o The mean difference is the mean difference between our test value (0) and the mean weekly allowance reported in the box labeled One-Sample Statistics. The mean difference is 7.24. If you select a test value that is not 0, your mean difference would not be the same as the mean. You will need to turn to Appendix B in your textbook to figure out what the t-critical value is. I would select for infinity, since my N is much greater than 120. Make your decision about what we should do with the obtained information. In your assignment, I have set your alpha value at 0.05 (α=0.05).   10 Independent Samples T-Test In the second portion of Project 3, you will conduct a two-tailed independent samples t-test. This is covered In more detail in the second half of the chapter on hypothesis testing. Once your data are open, click “Analyze”, then “Compare Means”, and finally “Independent Samples T Test” to open the menu to conduct the independent samples t-test.     You will need to select your test variable and your grouping variable. In this case, I will select H2EE8 as my test variable and BIO_SEX2 as the grouping variable. BIO_SEX2 is the variable for sex. Click the arrow next to “Test Variables” to select H2EE8 as the test variable, and the arrow next to “Grouping Variable” to define BIO_SEX2 as our grouping variable. From here, you will need to click “Define Groups…” to tell SPSS which two categories we will use, to see if there is a difference in our test variable. Make sure the bubble next to “Use specified values” is selected. Next, you will need to type the number “1” in the Group 1 box and “2” in the Group 2 box. What this means, as it will mean in your project, is that Group 1 = male and Group 2 = female. So we will see if there is a significant difference in adolescents’ allowances by gender. Ta da! Click “Continue”. Notice that in the parenthetical note next to BIO_SEX2 it says (1 2)? This means it will compare the differences between these two groups. If you do not define the groups, SPSS will not run the test. If you used a variable with more than 2 categories, you would need to make sure you were comparing the two groups you intended to compare. Now click OK. 11  The output window should display something similar to the following:   Let’s start off with the first box, labeled “Group Statistics.” Here we can see the mean, standard deviation, and standard error of the mean for Male and Female. So we can see that the mean allowance for males was 6.77, while for females it was 7.67. Similarly, we can see the standard deviations and standard errors of the mean, too. Just by looking at the Group Statistics table, we can see that it looks like females earn higher weekly allowances and their standard deviations suggest more variability than for males. This alone cannot tell us if there are significant differences in allowance, between men and women. Next, look at the Independent Samples Test table. For the purposes of this assignment, you need to look at the data where equal variances are assumed. This is similar to what we have covered in the memos and the second half of the chapter on hypothesis testing. Look at all the information under t-test for Equality of Means test. This just means that SPSS is showing us if the mean allowance amount is actually the same. Our obtained t-statistic shows up under the column labeled t. It is -2.817. The degrees of freedom are labeled as df. df=4777.     Our P-value is labeled as Sig. (2-tailed).      The mean difference is -0.901, and the standard error of the difference is 0.320. Now look back to the Group Statistics table. We can see that the mean difference suggests that males (Group 1) earn about 90 cents less than females (Group 2) in their weekly allowances. If you label males as Group 2, and females as Group 1, the mean difference would be positive, as would your obtained t-statistic. You will need to turn to Appendix B in your textbook to figure out what the t-critical value is. I would select for infinity, since my N is much greater than 120. Make your decision about what we should do with the obtained information. In your assignment, I have set your alpha value at 0.05 (α=0.05). Please let me or your course mentor know if something is not clear or if you have questions. 12 SECTION D: RUBRIC PART ONE: SINGLE-SAMPLE HYPOTHESIS TEST NOTE: Credit may be deducted throughout for messy/unpresentable work. Introduction and descriptive statistics CHECK PLUS (excellent/mastery): All statistics and parameters have been reported. Best measures are selected and described (accurately with justification). Critical reflection about the level of measurement has been discussed. References to the sample/population have been made. Referees previous research. CHECK (basic/average): All statistics and parameters have been reported. Reasonable measures are selected and described with varying degrees of depth or correctness. Less-critical reflection has been made or less reasonable descriptions provided. Missing discussion of previous research. CHECK MINUS (below average): Some required statistics have not been reported OR all have been reported but there are some inaccuracies. Little, no, or inaccurate measures selected for description. Absence of or incorrect reflection provided. Hypothesis statement FULL CREDIT: Two-tailed hypotheses appropriately stated using symbols and/or words. HALF CREDIT: Some problems with stating the two-tailed hypotheses appropriately. One of the hypotheses may be missing. NO CREDIT: Significant problems stating the two-tailed hypotheses appropriately. One or both may be missing. Annotated test statistics CHECK PLUS: All required statistics have been included and are labeled appropriately. Interpretations reflect mastery of statistics. CHECK: All required statistics have been included and are labeled appropriately. Interpretations reflect basic or below average comprehension of statistics. CHECK-MINUS: Errors in labeling or some missing statistics or interpretations. CheckPlus 10 Check 7.5 CheckMinus 5 10 5 0 10 7.5 5 Hypothesis decision FULL CREDIT. Correct decision/interpretation of results. Uses technical language. HALF CREDIT. More or less correct decision/interpretation of results. NO CREDIT: Incorrect decision and lacks understanding of subject matter. 5 2.5 0 Reflection This is your opportunity to demonstrate what you know about the data, the statistics you performed, and the information you've inferred from those statistics (that is, what do they SAY?). CHECK-PLUS. Above-and-beyond effort. Response demonstrates mastery of subject matter. Excellent explanation of accurate results in line with the information provided. The interpretation is between 5 and 7 sentences length. CHECK. Typical effort. Response demonstrates average, though correct, understanding of subject matter. Appropriate, though superficial explanation of the results. They are in line with the information provided. The interpretation is between 5 and 7 sentences in length. CHECK-MINUS. Below-average effort. Response demonstrates incomplete or incorrect understanding of subject matter. The explanation is not effective. It is short or demonstrates significant misunderstandings of one-sample t-statistic interpretations. 10 7.5 5 N/C 0 0 0 PART TWO: INDEPENDENT-SAMPLES HYPOTHESIS TEST 13 Grouping variable information CHECK PLUS (excellent/mastery) : All statistics and parameters have been reported. Best measures are selected and described (accurately with justification). Critical reflection about the level of measurement has been discussed. References to the sample/population have been made. Referees previous research. CHECK (basic/average): All statistics and parameters have been reported. Reasonable measures are selected and described with varying degrees of depth or correctness. Less-critical reflection has been made or less reasonable descriptions provided. Missing discussion of previous research. CHECK MINUS (below average): Some required statistics have not been reported OR all have been reported but there are some inaccuracies. Little, no, or inaccurate measures selected for description. Absence of or incorrect reflection provided. Hypothesis statement FULL CREDIT: ONE-tailed hypotheses appropriately stated using symbols and/or words. HALF CREDIT: Some problems with stating the ONE -tailed hypotheses appropriately. One of the hypotheses may be missing. NO CREDIT: Significant problems stating the ONE -tailed hypotheses appropriately. One or both may be missing. Annotated test statistics CHECK PLUS: All required statistics have been included and are labeled appropriately. Interpretations reflect mastery of statistics. CHECK: All required statistics have been included and are labeled appropriately. Interpretations reflect basic or below average comprehension of statistics. CHECK-MINUS: Errors in labeling or some missing statistics or interpretations. Hypothesis decision FULL CREDIT. Correct decision/interpretation of results. Uses technical language. HALF CREDIT. More or less correct decision/interpretation of results. NO CREDIT: Incorrect decision and lacks understanding of subject matter. 10 7.5 5 0 10 5 0 10 7.5 5 5 2.5 0 Reflection This is your opportunity to demonstrate what you know about the data, the statistics you performed, and the information you've inferred from those statistics (that is, what do they SAY?). CHECK-PLUS. Above-and-beyond effort. Response demonstrates mastery of subject matter. Excellent explanation of accurate results in line with the information provided. The interpretation is between 5 and 7 sentences length. CHECK. Typical effort. Response demonstrates average, though correct, understanding of subject matter. Appropriate, though superficial explanation of the results. They are in line with the information provided. The interpretation is between 5 and 7 sentences in length. CHECK-MINUS. Below-average effort. Response demonstrates incomplete or incorrect understanding of subject matter. The explanation is not effective. It is short or demonstrates significant misunderstandings of one-sample t-statistic interpretations. Peer Evaluation The best replies will make specific references to project issues, contain at least three to five sentences, and are respectful and constructive. Students should demonstrate mastery of course concepts in their replies. Points lost for repetition, glad-handing, and non-constructive feedback. 10 7.5 5 0 10 7.5 5 0 0 14 SECTION E: EXAMPLE PROJECT The following example demonstrates how a PROJECT might look. The data in this sample is derived from another source and some information has been redacted to reduce copying. ---------------------------------------------------------------------------------------------------------------------------------TEST ONE: SINGLE-SAMPLE HYPOTHESIS TEST 1. Introduction and descriptive statistics The variable I chose to analyze comes from the 2008 GSS and is called “hrs1,” or “number of hours worked last week.” This variable measures how many hours people typically work in a week. I think that number of hours worked in a week is appropriately measured at an interval/ratio level (that is, the distance between each category is equidistant) and will be suitable for a t-test. For this project, I’ll treat this data as my population – that is, the US population. It appears here that US residents work, on average, 42 hours per week; however the median and mode indicate 40 hours, so there are people who are working many more than 40 a week. I can see that the highest reported time is 89 -- so some people are working more than full-time hours. The standard deviation is REALLY high so we can tell there is a lot of difference in the amount of weekly hours worked in this sample. According to the Bureau of Labor Statistics, this is typical, though there is some fluctuation based on gender and full/part time status. SOURCE: http://www.bls.gov/opub/ted/2015/time-spent-working-by-fulland-part-time-status-gender-and-location-in-2014.htm.          N=744 mean: 42 median: 40 mode: 40 standard deviation: 14.48 standard error: .417 minimum value: 1 maximum value: 89 range: 88 2. Hypotheses Statement In a smaller (hypothetical) survey I recently gave, the mean number of hours of work was 40 (m=40 hours; n=85 people). However, the mean number of hours worked by 2008 GSS data (which I’m treating as my population) is 42 hours. Is my sample data different than the population data? I am interested in finding out whether this difference is statistically significant, or whether the difference can be attributed to sampling error. My null hypothesis is that there is no statistically significant difference between the mean “number of hours worked last week” and a “typical” 40-hour work week. My research hypothesis is that there is a statistically significant difference between the mean “number of hours worked last week” and a 40-hour work week. 3. Annotated one-sample t-test statistics:    mean difference: 2.003. A mean difference of 2 indicates that ________. degrees of freedom: 1202. The df for this test is 1202, which indicates that _______. obtained t-statistic: 4.799 My t-obtained is 4.799, which indicates that _______. 15   t-critical: +/- 1.960. My t-critical is 1.960, which is _________ compared with my t-obtained of 4.799. p-value: 0.000. A p-value of "0" indicates that _______. 4. Hypotheses decision: Is this a significant mean difference between your class data and the population? Report your decision as whether you accept or reject the null hypothesis and why you came to this decision. (1-2 sentences). We are evaluating your ability to read, interpret, and report findings from statistical tests. 5. Reflection: In addition to a description of the type of statistical test performed here, explain these measures you have now obtained and reported and explain what they mean. Explain your results in a ‘real world’ context. My analysis shows that despite the rather small practical difference between the mean “number of hours worked last week” and a “typical” 40-hour work week (2.003 hours), that this difference is nevertheless statistically significant. We thus have sufficient evidence to conclude that the number of hours worked per week in 2008 were significantly higher than the “typical” 40-hour work week observed in my sample. and the difference is significant at the .05 level. I wonder why people in my survey worked fewer hours than a typical workweek of 42 hours? TEST TWO: INDEPENDENT-SAMPLES HYPOTHESIS TEST For Part 2, I will examine whether there is mean difference in poor mental health days by gender. 6. Grouping variable information: For my tests, I selected poor mental health (over the past month; measured at an interval-ratio level) and gender (a dichotomous sorting variable). Poor Mental health days is ideally measured at an interval-ratio level because each day is equidistant from the other. The variable may not fully tap a person's actual mental health because they may have had a major sad life event rather than be in poor mental health. I elected to look at gender differences in mental health because there is a lot of literature about these issues. When it comes to gender, women and men may have similar rates of mental illness; however, women may report or experience more depression than their men counterparts, who tend to externalize in the form of antisocial behavior. It looks like the typical person in the sample will report one poor mental health day; however, the average is 3.79, so there are some people who suffer more than 20 days a month (skewing the data). This observation is confirmed because I can see that the standard deviation is over 6 days and the range is the maximum amount (i.e., 30 days). The sample is 51% man-identified which is a little different than the actual representation of men in the population, but that shouldn't affect our results much. SOURCE: http://apps.who.int/iris/bitstream/10665/68884/1/a85573.pdf It appears here that, as I kind of expected, women report more poor mental health days in the past month than men by one day. The standard deviations are still quite high for each group, so I expect there to be similar variation in each grouping.  Group 1: Men (they are coded "1" in the data) o Mean days of poor mental health in past month: 3.43 o Standard Deviation: 6.314 o Standard Error of Mean: .321 16  Group 2: Women (they are coded "2" in the data) o Mean days of poor mental health in past month:: 4.18 o Standard Deviation: 6.644 o Standard Error: .351 7. Hypotheses Gender differences: My null hypothesis states that there is not a statistically significant difference in the mean days of poor mental health between women and men. My research hypothesis is that there is a statistically significant difference in the mean days of poor mental health between women and men – I suspect women would have MORE poor mental health days. 8. T-test Information:  BY GENDER: o Mean Difference: -0.752. A mean difference of -0.752 indicates that ________. o Std. Error of the difference: .475 o Obtained t-statistic: -1.582. My t-obtained is -1.582, which indicates that _______. o Degrees of Freedom: 742. The df for this test is 742, which indicates that _______. o t-critical: +/- 1.960 (I had to use Appendix B!) My t-critical is 1.960, which is _________ compared with my t-obtained of -1.582. o p-value: < .0001. A p-value of ".0001" indicates that _______. 9. Decisions based on hypotheses: Is this a significant mean difference between your two groups with respect to your outcome variable? Did women have more poor mental health days than men? Report your decision as whether you accept or reject the null hypothesis and why you came to this decision. (1-2 sentences). We are evaluating your ability to read, interpret, and report findings from statistical tests. 10. Results and Reflection: In a full paragraph, provide an informed reflection. Using your one external resource, information about the statistics you performed, your data, and the samples and populations you’re testing, critically reflect on your analysis. You should consider the following questions: What does a previous study related to this information tell us? Why do you think you obtained this result? What does it mean? Is your variable measured in the best way possible? What do the results of your test indicate? What do your findings say about the sample? Is it generalizable to the world? A type of population? Are your findings consistent with other findings? (HINT: I list which countries we may compare our data in the codebook?) What other variables in the codebook might these variables be related to? 17 
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