Stat report

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SOC 304 – Social Statistics STATISTICAL REPORT Your statistical report is based on demonstrating three skills: - Your ability to use SPSS in order to generate the findings needed for the write-up of your report Your ability to do some calculation of statistics based on some findings from the output. Your ability to interpret and make sense of your output. This report is a means to assess your level of quantitative literacy (see rubric table attached at the end of this document). Your quantitative report should be organized as follows: 1. Analysis: Answer ALL questions below as each step is graded. Having the answers ready on this word document will help you submit the graded answers in the Statistical Literacy report quiz. Submit your answers via the Statistical Literacy Report Quiz on D2L. You have unlimited attempts. Don’t press the submit button unless you are done. There is no time limit. There is however a deadline. 2. Submit in the Statistical Literacy Report assignment dropbox: your complete SPSS output used for the analysis (you can export your output as an RTF file or you can copy and paste into your word document) and submit it in the dropbox for the “Statistical Project.” Note that the deadline for the output is earlier than the Statistical Literacy Report. I will be checking your output file to see if you made some Guidelines/requirements for the analysis to find under this module “Statistical Literacy Report”: 1. You will need to use the GSS 2014 data (GSS2014.sav) file (available on D2L) 2. You will need to use the Fall 2018 SCSU survey SPSS data file (FallSurvey2018_SOC 304.sav file) (available on D2L). 3. Remember that you can only open this SPSS (.sav) files from SPSS accessed via Apps Anywhere AFTER you have uploaded those files using Web/Files Space (See “how to” Adobe Recording on D2L) SOC 304 – Social Statistics 1. UNIVARIATE ANALYSIS (31 POINTS) This section 1 on univariate analysis is based on using both data sets (GSS 2014 and SCSU 2018 Fall survey). Remember to choose appropriate measures of descriptive statistics based on the level of measurement of each variable. In addition, for EACH variable, you need to describe with one sentence or two the descriptive statistics you computed. Nominal and ordinal variables require you to mention valid percent (not percent) . For the univariate analysis of HRS1 and HRSRELAX, provide the mean and the standard deviation. 1) SEX. a. In your GSS 2014 file, describe the SEX composition. Use valid percent in your statement. (1 point) b. Also, based on this data file, and this SEX variable, what is the ratio of men to women? For every 10 women, there are ___ men. (1 point) c. In your SCSU 2018 Fall survey file, describe the sex composition (use the SGender variable). Use valid percent in your statement. (1 point) d. Also, Also, based on this data file, and this SGender variable, what is the ratio of men to women? For every 10 women, there are ___ men. (1 point) 2) HRSRELAX. (“After an average work day, about how many hours do you have to relax or pursue activities that you enjoy?”) (from the GSS 2014 file) a. Provide the mean and standard deviation. (2 points) b. provide the values for approximately 68% of the middle respondent sample (between – 1 and +1 SD). (2 points) c. For HRSRELAX, compute the confidence interval and provide the following missing information. (2 points) At a 99% confidence level, the confidence interval for the population mean of HRSRELAZ is between ____ and ____. (Hint: you need to use the EXPLORE menu from ANALYZE and change the confidence level in “Statistics” from 95 to 99) 3) CHILDS. (from the GSS 2014 data file) a. Recode CHILDS into CHILDSR with only 4 categories so as “0,” “1,” “2,” are coded respectively “0,” “1,” and “2” and collapse values “3” through “8” into value “3.” Label the values of your new variable CHILDSR (in the SOC 304 – Social Statistics variable view window) so that “0” = “no children,” “1” = “1 child,” “2” = “2 children,” and “3” = “3 children or more.” (See the SPSS primer for using the “transform into different variable” instructions). Then run a frequency distribution of CHILDSR making sure the value labels are visible on your table. Fill in the blank. There are ___ respondents who have 3 children or more. (.5 point) b. Use valid percent to describe CHILDSR in your statement. (2 points) 4) HRS1. (from the GSS 2014 data file) a. Provide the mean and standard deviation. (2 points) b. provide the values for approximately 68% of the middle respondent sample (between – 1 and +1 SD). (2 points) 5) Q28IMM_MUS1. (SCSU 2018 Fall survey file) a. Use valid percent values to describe respondents’ stand on the statement “Muslim immigrants are more difficult to integrate into American society because of their religion.” Treat values 88, and 99 as missing (see “using SPSS primer” specific to missing and recoding or the Adobe Connect recording for SPSS assignments 11, 12, and 13). Make sure you set the missing values so that you end up with only 5 categories (strongly agree, somewhat agree, neutral, somewhat disagree, and strongly disagree). Set “Don’t Know” and “Refused” as system missing. Remember that you can set the missing values on the variable view window in the “missing” cells for that variable. (2.5 points) b. Then adding valid percentages, fill in the blanks. ___ % of respondents overall agree with this statement compared to ___ % disagree with this statement. (2 points) 6) Q16JOB_TRUMP. (SCSU 2018 Fall survey file) a. Use valid percent values to describe respondents’ rating of president Trump’s overall performance. Treat values 88 and 99 as missing values. Make sure you set the missing values so that you end up with only 5 categories (Excellent, pretty good, only fair, poor, very poor). Remember that you can set the missing values on the variable view window in the “missing” cells for that variable (2 points). b. Then adding valid percentages, fill in the blanks. ____ % of all respondents who answered this question rate president Trump at least as SOC 304 – Social Statistics “pretty good” compared to ____ % who view president Trump at the best as “pretty poor.”. (2 points) 7) Q5PARTY1 (SCSU 2018 Fall survey file) a. Only set “refused” value 99 as missing. NOTE: In part 5 of this assignment, you will need to set values 3 to 9 as missing system (SYSMIS) using the recoding into a different variable command so that you are only looking at 2 categories (Democrat and Republican). Run the frequency distribution of Q5PARTY1. b. The number of respondents who see themselves as “Not political” is ____. (1 point) c. Use valid percent values to describe respondents’ political affiliation. (5 points) 2. COMPARING TWO GROUPS MEANS (15 POINTS) For this section, you need to use the GSS 2014 data. Does SEX of the respondent matter in terms of how many hours one has to relax at the end of the day? Run the independent samples T-test on SPSS in order to answer this question. You will need to select “Options” to get some information about sample means. Hint: Pay attention to the value numbers for male and female when selecting two groups to run the independent samples T-test. (See SPSS assignment covering chapter 9 for illustration) Make sure you review the chapter on two-independent samples testing before you do the following: a. Run the independent samples T-test on SPSS (make sure the output for this is in the output file submitted in the dropbox (2 points) b. Address the 3 required assumptions (Step 1 of hypothesis testing) (2 points) c. State the hypotheses (H0 and H1) (1 point) d. Provide values for sample means of each subgroup/categorical group. (2 points) e. Calculate the sample mean difference between those two groups. (1 point) f. Provide the value of the obtained t. (1 point) g. Provide probability of t (p-value for T). Hint: look for “sig.” (1 point) SOC 304 – Social Statistics h. Answer the following question. Based on the number found for the pvalue, did the test statistic fall into the critical region? If so, at what alpha level (.05?, .02?, .01?, .001?)? Remember that the P-value must be smaller than the alpha and that we want to use the smallest alpha as possible (2 points) i. Make a decision (Reject or fail to reject) (1 point) j. Interpret the results in terms of what you were testing and what it means in comparing those two groups on your dependent variable. (2 points) 3. ANALYSIS OF VARI ANCE – ANOVA (18 POINTS) You are still using GSS 2014 in this section. You will need to run a “One-Way ANOVA” in order to answer the following question. Use HRSRELAX in the “dependent list” and CHILDSR in “factor.” Also, make sure you select “Descriptive” from the “Options” menu as well as “Bonferroni” from the “Post Hoc…” menu. (See SPSS assignment 10 covering ANOVA for illustration) Does the number of children matter in terms of how many hours to relax respondents have? a. Run ANOVA (make sure the output is in the dropbox) b. Address the 4 required assumptions (Step 1 of hypothesis testing). (4 points) c. State the hypotheses. (2 points) d. Provide the value of the F ratio (obtained) (1 point) e. Provide probability of F ratio (obtained) or the P-value of F. (1 point) f. Indicate from your output how was calculated the MSW and MSB. Hints: Use the actual values from the output. (4 points) MSW = _____ / _____. MSB = _____ /___. g. Use your results from the Bonferroni post hoc test in order to interpret the mean difference between each of the three categorical groups. You should describe the mean differences regarding statistical significance. For each comparison you need to provide the value for the mean difference as well as information about being statistically significant at .05. Hint: Look for stars. For each two groups comparison, make a statement about the difference in means between these groups. For instance, “there SOC 304 – Social Statistics is no statistically significant mean difference between democrats and republicans.” If you have a total of 4 categories, you need to make 6 comparative statements (group 1 with group 2, group 1 with group 3, group 1 with group 4, group 2 with group 3, group 2 with group 4, group 3 with group 4). (6 points) 4. CORRELATION AND COEFFICIENT OF DETERMINATION (5 POINTS) Now using HRS1 and HRSRELAX, what is the relationship between the number of hours one works and number of hours to relax? Review chapter 13 for this section. a. Run a bivariate correlation between those two variables. b. Provide the value for Pearson’s r. (1 point) c. Provide the significance level for Pearson’s r (P-value). Is r statistically significant? At what alpha level? (0.5 point) d. Interpret (based on r) the strength of the relationship, the direction of the relationship and pattern between those two variables (Greater the number of working hours per week…). (1.5 points) e. Calculate r2 based on r and interpret r2 as a PRE measure. Hints: how much is explained by the variance in …) (2 points). 5. NOMINAL AND ORDINAL BIVARIATE RELATIONSHIPS (31 POINTS) In this section, you need to use the SCSU Fall 2018 data file. Make sure you have dealt with missing values prior to exploring those relationships. Explore the following relationships. 1. Does being a democrat or a republican matter in terms of agreeing or disagreeing with the statement “Muslim immigrants are more difficult to integrate into American society because of their religion”? Hint: you need to create a new variable called PARTYR recoding the Q5PARTY1 variable and setting as system missing (SYSMIS any value that is NOT either democrat or republican (values 3-9). You should then end up with a binary variable (dichotomous variable). You will also need to use the dependent variable “Q28IMM_MUS1.” Make sure you set the missing values so that you end up with only 5 categories (strongly agree, somewhat agree, neutral, somewhat disagree, and strongly disagree). SOC 304 – Social Statistics Remember that you can set the missing values on the variable view window in the “missing” cells for that variable. (15.5 points) 2. Does the rating of Trump’s overall performance matter in predicting attitudes towards the statement “Muslim immigrants are more difficult to integrate into American society because of their religion”? Use the variable “Q28IMM_MUS1” as previously used (only 5 categories) as the dependent variable. Use the variable “Q16JOB_TRUMP” after making sure that you only keep 5 categories (Excellent, Pretty good, Only fair, Poor, Very poor). (15.5 points) For each of them (1. And 2.) you need to do the following: k. Run appropriate bivariate tables (column percentages). Hint: make sure you select the appropriate variable for column or row and that you check “column” percentage in the “cells” option. l. Interpret percent values in cell (you need to write sentences that includes percentages for each cell). Remember to compare percentages across after you obtain them within each column. (2 points) m. State the hypotheses for Chi-square, (1 point) n. compute Chi-square and provide the value of Chi-square, (1 point) o. What is the p-value (sig.) for Chi-square? State the alpha level for Chisquare. Is it statistically significant? If so, at .05? at .01? at .001? (2 points) p. Make a statement about your decision to reject/fail to reject the null hypothesis, (1 point) q. Interpret the results from chi-square (be specific about the variables). Is there a relationship between those variables? (1 point) r. Compute the appropriate measure of association (pay attention to level of measurement of each variable). Use Cramer’s V and Lambda for nominal variables. (2 points) Use Gamma for ordinal variables. (1 point) s. State the alpha level (p-value) associated with that measure of association. (2 points) t. Describe the: i. Strength of the relationship (weak, moderate, strong) while providing the value of the measure of association, (1 point) ii. Pattern of the relationship (Example: Democrat respondent are more likely to… than…) reading the bivariate table’s column percentages across, (1 point) iii. Direction of the relationship when appropriate (positive/negative) based on your measure of association. (1 point) SOC 304 – Social Statistics u. Use the measure of association that is appropriate for PRE and provide the PRE value in % in a sentence interpreting the bivariate relationship. (1.5 points) SOC 304 – Social Statistics Capstone 4 Interpretation Ability to explain information presented in mathematical forms (e.g., equations, graphs, diagrams, tables, words) Representation Ability to convert relevant information into various mathematical forms (e.g., equations, graphs, diagrams, tables, words) Calculation Milestones 3 2 1 Provides accurate explanations of information presented in mathematical forms. Makes appropriate inferences based on that information. For example, accurately explains the trend data shown in a graph and makes reasonable predictions regarding what the data suggest about future events. Provides accurate explanations of information presented in mathematical forms. For instance, accurately explains the trend data shown in a graph. Provides somewhat accurate explanations of information presented in mathematical forms, but occasionally makes minor errors related to computations or units. For instance, accurately explains trend data shown in a graph, but may miscalculate the slope of the trend line. Attempts to explain information presented in mathematical forms, but draws incorrect conclusions about what the information means. For example, attempts to explain the trend data shown in a graph, but will frequently misinterpret the nature of that trend, perhaps by confusing positive and negative trends. Skillfully converts relevant information into an insightful mathematical portrayal in a way that contributes to a further or deeper understanding. Competently converts relevant information into an appropriate and desired mathematical portrayal. Completes conversion of information but resulting mathematical portrayal is only partially appropriate or accurate. Completes conversion of information but resulting mathematical portrayal is inappropriate or inaccurate. Calculations attempted are essentially all successful and sufficiently comprehensive to solve the problem. Calculations are also presented elegantly (clearly, concisely, etc.) Calculations attempted are essentially all successful and sufficiently comprehensive to solve the problem. Calculations attempted are either Calculations are attempted unsuccessful or but are both unsuccessful and are not represent only a portion of the comprehensive. calculations required to comprehensively solve the problem. SOC 304 – Social Statistics Application / Analysis Uses the quantitative analysis Uses the quantitative analysis of Uses the quantitative analysis of Uses the quantitative of data as the basis for deep data as the basis for competent data as the basis for workmanlike analysis of data as the Ability to make judgments and and thoughtful judgments, judgments, drawing reasonable and (without inspiration or nuance, basis for tentative, basic draw appropriate drawing insightful, carefully appropriately qualified conclusions ordinary) judgments, drawing judgments, although is conclusions based on the qualified conclusions from this from this work. plausible conclusions from this hesitant or uncertain about quantitative analysis of data, work. work. drawing conclusions from while recognizing the limits of this work. this analysis Assumptions Ability to make and evaluate important assumptions in estimation, modeling, and data analysis Communication Explicitly describes assumptions and provides compelling rationale for why each assumption is appropriate. Shows awareness that confidence in final conclusions is limited by the accuracy of the assumptions. Explicitly describes assumptions and provides compelling rationale for why assumptions are appropriate. Explicitly describes assumptions. Uses quantitative information Uses quantitative information in Uses quantitative information, but in connection with the connection with the argument or does not effectively connect it to Expressing quantitative argument or purpose of the purpose of the work, though data the argument or purpose of the evidence in support of the work, presents it in an may be presented in a less than work. argument or purpose of the effective format, and completely effective format or some work (in terms of what explicates it with consistently parts of the explication may be evidence is used and how it is high quality. uneven. formatted, presented, and contextualized) Attempts to describe assumptions. Presents an argument for which quantitative evidence is pertinent, but does not provide adequate explicit numerical support. (May use quasiquantitative words such as "many," "few," "increasing," "small," and the like in place of actual quantities.)
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