ONEWAY alcohol BY ratingSTATISTICS DESCRIPTIVES HOMOGENEITY.docx

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ONEWAY alcohol BY rating /STATISTICS DESCRIPTIVES HOMOGENEITY /PLOT MEANS /MISSING ANALYSIS /POSTHOC=TUKEY ALPHA(0.05). Oneway Notes Output Created 07-JUN-2013 12:39:57 Comments Input Data C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Active Dataset DataSet1 File Label SPSS/PC+ Filter Weight Split File N of Rows in Working Data File 35 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics for each analysis are based on cases with no missing data for any variable in the analysis. Syntax ONEWAY alcohol BY rating /STATISTICS DESCRIPTIVES HOMOGENEITY /PLOT MEANS /MISSING ANALYSIS /POSTHOC=TUKEY ALPHA(0.05). Resources Processor Time 00:00:00.33 Elapsed Time 00:00:00.42 [DataSet1] C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Descriptives Alcohol by Volume (in %) for brand N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Lower Bound Upper Bound VeryGood 11 4.9000 .17889 .05394 4.7798 5.0202 Good 14 4.6000 .38829 .10377 4.3758 4.8242 Fair 10 4.5100 .34140 .10796 4.2658 4.7542 Total 35 4.6686 .35295 .05966 4.5473 4.7898 Descriptives Alcohol by Volume (in %) for brand Minimum Maximum VeryGood 4.70 5.20 Good 4.00 5.50 Fair 3.90 5.00 Total 3.90 5.50 Test of Homogeneity of Variances Alcohol by Volume (in %) for brand Levene Statistic df1 df2 Sig. 1.420 2 32 .256 ANOVA Alcohol by Volume (in %) for brand Sum of Squares df Mean Square F Sig. Between Groups .906 2 .453 4.357 .021 Within Groups 3.329 32 .104 Total 4.235 34 Post Hoc Tests Multiple Comparisons Dependent Variable: Alcohol by Volume (in %) for brand Tukey HSD (I) Rated Quality of Brand (J) Rated Quality of Brand Mean Difference (I-J) Std. Error Sig. VeryGood Good .30000 .12995 .069 Fair .39000 * .14093 .025 Good VeryGood -.30000 .12995 .069 Fair .09000 .13354 .780 Fair VeryGood -.39000 * .14093 .025 Good -.09000 .13354 .780 Multiple Comparisons Dependent Variable: Alcohol by Volume (in %) for brand Tukey HSD (I) Rated Quality of Brand (J) Rated Quality of Brand 95% Confidence Interval Lower Bound Upper Bound VeryGood Good -.0193 .6193 Fair .0437 * .7363 Good VeryGood -.6193 .0193 Fair -.2382 .4182 Fair VeryGood -.7363 * -.0437 Good -.4182 .2382 *. The mean difference is significant at the 0.05 level. Homogeneous Subsets Alcohol by Volume (in %) for brand Tukey HSD a,b Rated Quality of Brand N Subset for alpha = 0.05 1 2 Fair 10 4.5100 Good 14 4.6000 4.6000 VeryGood 11 4.9000 Sig. .784 .082 Means for groups in homogeneous subsets are displayed. a. Uses Harmonic Mean Sample Size = 11.436. b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not guaranteed. Mean.

Mean
Std. Deviation
Std. Error
95% Confidence Interval for Mean
Lower Bound
Upper Bound
VeryGood
11
4.9000
.17889
.05394
4.7798
5.0202
Good
14
4.6000
.38829
.10377
4.3758
4.8242
Fair
10
4.5100
.34140
.10796
4.2658
4.7542
Total
35
4.6686
.35295
.05966
4.5473
4.7898

Mean Difference (I-J)
Std. Error
Sig.
VeryGood
Good
.30000
.12995
.069
Fair
.39000
*
.14093
.025
Good
VeryGood
-.30000
.12995
.069
Fair
.09000
.13354
.780
Fair
VeryGood
-.39000
*
.14093
.025
Good

means are statistically significantly different for the others.
Using the results of the Tukey HSD post hoc test, what two
quality rating groups had significantly different mean alcohol
by volume levels? How do you know?
Requirements
How do you get the answer and what do you understand about
it?

SPSS Data Interpretation Alcohol Volume A between-group one-way analysis of variance (ANOVA) compares the mean values of more than two groups. In this assignment, you will review the SPSS output for an ANOVA and use it to answer questions about the means of the groups. Directions: Review the SPSS output file, which reports the results of the between-group (independent group) one-way ANOVA to see if the mean alcohol by volume (%) of the beer differs as a function of quality of the brand as rated by a beer expert (in 2012). Answer the following questions based on your observations of the SPSS output file: 1. Looking at the descriptives (first information), do you see differences in the mean alcohol contents for the three levels of quality? Explain. 1. Looking at the Test for Homogeneity of Variances (Levene Statistic), is it reasonable to proceed with the ANOVA? Is the assumption met, or violated? How do you know? 1. Looking at the results of the ANOVA, is there a significant difference in the mean alcohol content for beers in the three quality groups? How do you know? Write the results in the following format: F(df value) = ___, p value = ______. 1. The pairwise post hoc tests indicate which quality groups' means are statistically significantly different for the others. Using the results of the Tukey HSD post hoc test, what two quality rating groups had significantly different mean alcohol by volume levels? How do you know? SPSS Data Set Legend (Attachment “A”) Information has been gathered on 35 brands of wheat beer. Qualitative (categorical) information has been given codes. Information that is in numerical form (e.g., $ amount) does not need to be coded. Here are all the types of information gathered on these beers: 1. Product name (abbreviation of product’s brand name) 2. Product ID code a. Codes: Each brand is given a numerical ID, with 1 being the first one to 35 for the last one 3. Rating assigned to the product by a taste expert for each brand a. Codes: 1 = Very good 2 = Good 3 = Fair 4. Recommended by leading beer connoisseur magazine? a. Codes: 0 = no 1 = yes 5. Country of origin for each brand: a. Codes: 1 = USA 2 = Canada 3 = France 4 = Holland 5 = Mexico 6 = Germany 7 = Japan 6. Availability in the USA for each brand a. Codes: 1 = National 2 = Regional 7. Price per 6-pack for each brand (values are in US Dollars) 8. Cost per 12 fluid ounces for each brand (values are in US Dollars) 9. Calories per 12 fluid ounces 10. Sodium per 12 fluid ounces for each brand (values are in milligrams, mg) 11. Alcohol by volume for each brand (values are percents, %) 12. Price class for each brand a. Codes: 0 = Not classified 1 = Super premium 2 = Premium 3 = Popular 13. Regular or reduced calorie for each brand a. Codes: 0 = Regular 1 = Reduced calorie 14. Number of US states in which brand was sold in 2008. 15. Number of US states in which brand was sold in 2012. Data Interpretation (Attachment “B”) ONEWAY alcohol BY r.

Can anyone helpme with this assignment below Need to pass Plagarism.docx

hacksoni

Can anyone helpme with this assignment below? Need to pass Plagarism TURN IT IN Software! CORRELATIONS /VARIABLES=calories alcohol /PRINT=TWOTAIL NOSIG /STATISTICS DESCRIPTIVES /MISSING=PAIRWISE. Correlations Notes Output Created 07-JUN-2013 13:24:52 Comments Input Data Active Dataset DataSet1 File Label SPSS/PC+ Filter Weight Split File N of Rows in Working Data File 35 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics for each pair of variables are based on all the cases with valid data for that pair. Syntax CORRELATIONS /VARIABLES=calories alcohol /PRINT=TWOTAIL NOSIG /STATISTICS DESCRIPTIVES /MISSING=PAIRWISE. Resources Processor Time 00:00:00.02 Elapsed Time 00:00:00.45 [DataSet1] C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Descriptive Statistics Mean Std. Deviation N Calories per 12 Fluid Ounces for brand 139.77 24.447 35 Alcohol by Volume (in %) for brand 4.6686 .35295 35 Correlations Calories per 12 Fluid Ounces for brand Alcohol by Volume (in %) for brand Calories per 12 Fluid Ounces for brand Pearson Correlation 1 .839 ** Sig. (2-tailed) .000 N 35 35 Alcohol by Volume (in %) for brand Pearson Correlation .839 ** 1 Sig. (2-tailed) .000 N 35 35 **. Correlation is significant at the 0.01 level (2-tailed). Review the SPSS output file which reports the results of the between-group (independent group) factorial ANOVA to see if the mean alcohol by volume (%) differs as a function of rating given by beer expert (IV 1) and/or recommendation made by a beer connoisseur magazine (IV 2). Answer the following questions based on your observations of the SPSS output file: Is the mean alcohol by volume level different for the type of rating given by the beer expert (main effect of IV1)? What are F-value and the significance level for this test (write result using the following notation: F (df1, df2) = _____, p = _____). Is the mean alcohol by volume level different for the type of recommendation given by the beer magazine? What are F-value and the significance level for this test (write result using following notation: F (df1, df2) = _____, p = _____). Is the mean alcohol by volume level different for different combinations of expert rating and magazine recommendation (interaction term)? What are F-value and the significance level for this test (write result using following notation: F (df1, df2) = _____, p = _____). Review the SPSS output file, which reports the results of computing the Pearson product-moment correlation coefficient to examine the possible relationship between the number of calories in a brand of beer and its alcohol by volume. Answer the following questions based on your observations of the SPSS output file: Looking at the correlations table, what is the r -value for the correlation between .

Review the SPSS output file which reports the results of the indepen.docx

ashane2

Review the SPSS output file which reports the results of the independent t-test to compare the mean price per 6-pack for regular vs. reduced calorie brands of wheat beer. Answer the following questions based on your observations of the SPSS output file: Is the F-value for Levene's Test for Equality of Variances significant (that is, is the p < .05)? What is the exact significance level? Note: if the Levene's Test for Equality of Variances is significant, then equal variances cannot be assumed. Which t- value should you use now that you know whether or not equal variances can be assumed? What is that t -value? What is the two-tailed significance level for that t -value? State the exact significance value. Report the results of the t -test as follows: t (df value) = ___, and p -value. Is there a statistically significant difference between the price per 6-pack of regular beers versus reduced calorie beers? T-TEST GROUPS=Reducedcals(0 1) /MISSING=ANALYSIS /VARIABLES=price /CRITERIA=CI(.95). T-Test Notes Output Created 07-JUN-2013 11:20:55 Comments Input Data C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Active Dataset DataSet1 File Label SPSS/PC+ Filter Weight Split File N of Rows in Working Data File 35 Missing Value Handling Definition of Missing User defined missing values are treated as missing. Cases Used Statistics for each analysis are based on the cases with no missing or out-of-range data for any variable in the analysis. Syntax T-TEST GROUPS=Reducedcals(0 1) /MISSING=ANALYSIS /VARIABLES=price /CRITERIA=CI(.95). Resources Processor Time 00:00:00.02 Elapsed Time 00:00:00.01 [DataSet1] C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Group Statistics Regular or reduced calorie for brand N Mean Std. Deviation Price per 6-pack for brand Regular 28 3.1154 1.24040 Reduced Calories 7 2.6757 .21870 Group Statistics Regular or reduced calorie for brand Std. Error Mean Price per 6-pack for brand Regular .23441 Reduced Calories .08266 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t Price per 6-pack for brand Equal variances assumed 6.987 .012 .924 Equal variances not assumed 1.769 Independent Samples Test t-test for Equality of Means df Sig. (2-tailed) Mean Difference Price per 6-pack for brand Equal variances assumed 33 .362 .43964 Equal variances not assumed 31.912 .086 .43964 Independent Samples Test t-test for Equality of Means Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Price per 6-pack for brand Equal variances assumed .47576 -.52829 1.40758 Equal variances not assumed .24856 -.06671 .94600 .

For this assessment, you will complete an SPSS data analys.docx

templestewart19

For this assessment, you will complete an SPSS data analysis report using a one-way ANOVA for assigned variables. We are often confronted with a need to compare the means of more than two groups. We may also need to compare more than two scores among a sample of participants. ANOVA, AN alysis O f VA ariance, is a technique designed to address such questions. SHOW LESS By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria: Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests. Develop a conclusion, including strengths and limitations of a one-way ANOVA. Competency 2: Analyze the decision-making process of data analysis. Analyze the assumptions of a one-way ANOVA. Competency 3: Apply knowledge of hypothesis testing. Articulate a research question, null hypothesis, alternative hypothesis, and alpha level. Competency 4: Interpret the results of statistical analyses. Interpret the one-way ANOVA output. Competency 5: Apply a statistical program's procedure to data. Apply the appropriate SPSS procedures to check assumptions and calculate the one-way ANOVA to generate relevant output. Competency 6: Apply the results of statistical analyses (your own or others) to your field of interest or career. Develop a context for the data set, including a definition of required variables and scales of measurement. Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. Communicate in a manner that is scholarly, professional, and consistent with expectations for members of the identified field of study. Competency Map CHECK YOUR PROGRESS Use this online tool to track your performance and progress through your course. Toggle Drawer ContextRead Assessment 4 Context [DOC] for important information on the following topics: SHOW LESS The logic of a one-way ANOVA. Avoiding inflated Type I error. Hypothesis testing in one-way ANOVA. Assumptions of one-way ANOVA. Toggle Drawer Questions to ConsiderAs you prepare to complete this assessment, you may want to think about other related issues to deepen your understanding or broaden your viewpoint. You are encouraged to consider the questions below and discuss them with a fellow learner, a work associate, an interested friend, or a member of your professional community. Note that these questions are for your own development and exploration and do not need to be completed or submitted as part of your assessment. SHOW LESS Application of F -Tests Is there a research question from your professional life or career specialization that can be addressed by a one-way ANOVA? Why would a one-way ANOVA be the appropriate analysis for this research question? What is the expected outco.

UNIANOVA alcohol BY rating Recommendation METHOD=SSTYPE(3) .docx

willcoxjanay

UNIANOVA alcohol BY rating Recommendation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=rating(TUKEY) /PLOT=PROFILE(rating*Recommendation) /EMMEANS=TABLES(OVERALL) /EMMEANS=TABLES(rating) /PRINT=ETASQ DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=rating Recommendation rating*Recommendation. Univariate Analysis of Variance Notes Output Created 07-JUN-2013 13:19:59 Comments Input Data C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Active Dataset DataSet1 File Label SPSS/PC+ Filter <none> Weight <none> Split File <none> N of Rows in Working Data File 35 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on all cases with valid data for all variables in the model. Syntax UNIANOVA alcohol BY rating Recommendation /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=rating(TUKEY) /PLOT=PROFILE(rating*Recommendation) /EMMEANS=TABLES(OVERALL) /EMMEANS=TABLES(rating) /PRINT=ETASQ DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=rating Recommendation rating*Recommendation. Resources Processor Time 00:00:00.36 Elapsed Time 00:00:00.73 [DataSet1] C:\Users\donn\Documents\GCU Lead fac\Project with Judy for modifying PSY845 to introduce SPSS\drinks database -revised for course applications DH.sav Between-Subjects Factors Value Label N Rated Quality of Brand 1 VeryGood 11 2 Good 14 3 Fair 10 Recommended by leading beer connoseur magazine in 2012 review 0 No 18 1 Yes 17 Descriptive Statistics Dependent Variable: Alcohol by Volume (in %) for brand Rated Quality of Brand Recommended by leading beer connoseur magazine in 2012 review Mean Std. Deviation N VeryGood No 4.7000 .00000 4 Yes 5.0143 .10690 7 Total 4.9000 .17889 11 Good No 4.3625 .24458 8 Yes 4.9167 .31252 6 Total 4.6000 .38829 14 Fair No 4.3333 .29439 6 Yes 4.7750 .22174 4 Total 4.5100 .34140 10 Total No 4.4278 .26965 18 Yes 4.9235 .23057 17 Total 4.6686 .35295 35 Tests of Between-Subjects Effects Dependent Variable: Alcohol by Volume (in %) for brand Source Type III Sum of Squares df Mean Square F Sig. Corrected Model 2.679a 5 .536 9.983 .000 Intercept 717.142 1 717.142 13361.573 .000 rating .494 2 .247 4.601 .018 Recommendation 1.559 1 1.559 29.041 .000 rating * Recommendation .084 2 .042 .785 .466 Error 1.556 29 .054 Total 767.080 35 Corrected Total 4.235 34 Tests of Between-Subjects Effects Dependent Variable: Alcohol by Volume (in %) for brand Source Partial Eta Squared Corrected Model .633a Intercept .998 rating .241 Recommendation .500 rating * Recommendation .051 Error Total Corrected Total a. R Squared = .633 (Adjusted R Squared = .569) Profile Plots Micro Chip Computer Corporation Selected Financial Data 2007 2006 2005 2004 2008 Micro Chip Computer Corporation Consolidated Statements of Operations F ...

Searching for help with this For this two-part assessment,.docx

rtodd280

Searching for help with this For this two-part assessment, you will respond to a question about interpreting correlations and use SPSS software to complete a data analysis and application report. You will examine three fundamental inferential statistics, including correlation, t tests, and analysis of variance (ANOVA). The first inferential statistic we will focus on is correlation, denoted r , which estimates the strength of a linear association between two variables. By contrast, t tests and ANOVAs will examine group differences on some quantitative dependent variable. SHOW LESS By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria: Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests. Develop a conclusion including strengths and limitations of correlation. Competency 2: Analyze the decision-making process of data analysis. Analyze the assumptions of correlation. Competency 3: Apply knowledge of hypothesis testing. Develop a research question, null hypothesis, alternative hypothesis, and alpha level. Competency 4: Interpret the results of statistical analyses. Interpret the correlation output. Competency 5: Apply a statistical program's procedure to data. Apply the appropriate SPSS procedures to check assumptions and calculate the correlations. Competency 6: Apply the results of statistical analyses (your own or others) to your field of interest or career. Develop a context for the data set, including a definition of required variables and scales of measurement. Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. Competency Map CHECK YOUR PROGRESS Use this online tool to track your performance and progress through your course. Toggle Drawer ContextRead Assessment 2 Context [DOC] for important information on the following topics: SHOW LESS Interpreting correlation: Magnitude and sign. Assumptions of correlation. Hypothesis testing of correlation. Effect size in correlation. Alternative correlation coefficients. Correlation—application. Proper reporting of correlations. r , degrees of freedom, and correlation coefficient. Probability values. Effect size. Toggle Drawer Questions to ConsiderAs you prepare to complete this assessment, you may want to think about other related issues to deepen your understanding or broaden your viewpoint. You are encouraged to consider the questions below and discuss them with a fellow learner, a work associate, an interested friend, or a member of your professional community. Note that these questions are for .

Introduction to spss

Manish Parihar

Review of "Survey Research Methods & Design in Psychology"

James Neill

2eda79c41aee471db842e8df57d4143f_7317.doc Your temporary usage period for IBM SPSS Statistics will expire in 13 days. GET FILE='C:\Documents and Settings\Administrator\Desktop\3303_Assign_December2014.sav'. DATASET NAME DataSet1 WINDOW=FRONT. UNIANOVA amount BY stomach weight /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(weight*stomach) /PRINT=ETASQ DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=stomach weight stomach*weight. Univariate Analysis of Variance Notes Output Created 23-DEC-2014 19:40:40 Comments Input Data C:\Documents and Settings\Administrator\Desktop\3303_Assign_December2014.sav Active Dataset DataSet1 Filter <none> Weight <none> Split File <none> N of Rows in Working Data File 78 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics are based on all cases with valid data for all variables in the model. Syntax UNIANOVA amount BY stomach weight /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(weight*stomach) /PRINT=ETASQ DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN=stomach weight stomach*weight. Resources Processor Time 00:00:01.38 Elapsed Time 00:00:02.16 [DataSet1] C:\Documents and Settings\Administrator\Desktop\3303_Assign_December2014.sav Between-Subjects Factors Value Label N stomach 1 empty 39 2 full 39 weight 1 underweight 26 2 normal 26 3 overweight 26 Descriptive Statistics Dependent Variable: amount stomach weight Mean Std. Deviation N empty underweight 24.92 5.330 13 normal 30.54 1.984 13 overweight 25.38 5.455 13 Total 26.95 5.124 39 full underweight 14.00 2.517 13 normal 12.00 1.472 13 overweight 22.77 6.796 13 Total 16.26 6.303 39 Total underweight 19.46 6.906 26 normal 21.27 9.606 26 overweight 24.08 6.183 26 Total 21.60 7.843 78 Tests of Between-Subjects Effects Dependent Variable: amount Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model 3335.141a 5 667.028 34.267 .000 .704 Intercept 36400.321 1 36400.321 1869.962 .000 .963 stomach 2229.346 1 2229.346 114.526 .000 .614 weight 281.256 2 140.628 7.224 .001 .167 stomach * weight 824.538 2 412.269 21.179 .000 .370 Error 1401.538 72 19.466 Total 41137.000 78 Corrected Total 4736.679 77 a. R Squared = .704 (Adjusted R Squared = .684) Profile Plots SORT CASES BY stomach. SPLIT FILE LAYERED BY stomach. ONEWAY amount BY weight /MISSING ANALYSIS /POSTHOC=TUKEY ALPHA(0.05). Oneway Notes Output Created 23-DEC-2014 20:26:34 Comments Input Data C:\Documents and Settings\Administrator\Desktop\3303_Assign_December2014.sav Active Dataset DataSet1 Filter <none> Weight <none> Split File stomach N of Rows in Working Data File 78 Missing Value Handling Definition of Missing User-defined missing values are treated as missing. Cases Used Statistics for each analysis are based on cases with no missing data for any variable in the analysis. Syntax ONEWAY amount BY weight /MISSING ANAL.

Btm8107 8 week6 activity apply repeated-measures a+ solution

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Maryland psyc 355 week 1 spss homework 1 new

uopassignment

Maryland psyc 355 week 1 spss homework 1 new

merlincarterr

Lecture 1

Konpal Darakshan

© Charles T. Diebold, Ph.D., 9152013. All Rights Reserved. .docx

LynellBull52

© Charles T. Diebold, Ph.D., 9/15/2013. All Rights Reserved. Page 1 of 16 Repeated Measures ANOVA Tutorial: RSCH-8250 Advanced Quantitative Reasoning Charles T. Diebold, Ph.D. September 15, 2013 How to cite this document: Diebold, C. T. (2013, September 15). Repeated measures ANOVA tutorial: RSCH-8250 advanced quantitative reasoning. Available from [email protected] Table of Contents Assignment and Tutorial Introduction ................................................................................................................ 2 Section 1: SPSS Specification of the Assignment ............................................................................................... 2 Descriptive Statistics ...................................................................................................................................... 3 Repeated Measures ANOVA ......................................................................................................................... 3 Section 2: Annotated Example SPSS Output, Write Up Guide, and Sample APA Table ..................................... 6 Descriptive Statistics ...................................................................................................................................... 6 Sphericity Assumption ................................................................................................................................... 7 Tests of Within-Subjects Effects .................................................................................................................... 7 Post Hoc: Profile Plot and Statistical Pairwise Comparison via Estimated Marginal Means ............................ 8 Tests of Within-Subjects Contrasts .............................................................................................................. 10 Test of Between-Subjects Effects ................................................................................................................. 10 Multivariate Tests for Repeated Measures .................................................................................................... 11 Results Write Up Guide ............................................................................................................................... 11 Sample APA Table ...................................................................................................................................... 12 For the Inquisitive: Sphericity and Within-Subjects Effects Redux ............................................................... 13 © Charles T. Diebold, Ph.D., 9/15/2013. All Rights Reserved. Page 2 of 16 Repeated Measures ANOVA Tutorial: RSCH-8250 Advanced Quantitative Reasoning Assignment and Tutorial Introduction This tutorial is intended to assist RSCH-8250 students in completing the Week 4 application assignment. I recommend that you use this tutorial as your first .

· Toggle DrawerOverviewFor this assessment, you will complete .docx

odiliagilby

· Toggle Drawer Overview For this assessment, you will complete an SPSS data analysis report using t-test output for assigned variables. You will review the theory, logic, and application of t tests. The t test is a basic inferential statistic often reported in psychological research. You will discover that t tests, as well as analysis of variance (ANOVA), compare group means on some quantitative outcome variable. SHOW LESS By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria: · Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests. 1. Develop a conclusion that includes strengths and limitations of an independent-samples t test. . Competency 2: Analyze the decision-making process of data analysis. 2. Analyze the assumptions of the independent-samples t test. . Competency 3: Apply knowledge of hypothesis testing. 3. Develop a research question, null hypothesis, alternative hypothesis, and alpha level. . Competency 4: Interpret the results of statistical analyses. 4. Interpret the output of the independent-samples t test. . Competency 5: Apply a statistical program's procedure to data. 5. Apply the appropriate SPSS procedures to check assumptions and calculate the independent-samples t test to generate relevant output. . Competency 6: Apply the results of statistical analyses (your own or others) to your field of interest or career. 6. Develop a context for the data set, including a definition of required variables and scales of measurement. . Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. 7. Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. Competency Map CHECK YOUR PROGRESSUse this online tool to track your performance and progress through your course. · Toggle Drawer Context Read Assessment 3 Context [DOC] for important information on the following topics: SHOW LESS . Logic of the t test. . Assumptions of the t test. . Hypothesis testing for a t test. . Effect size for a t test. . Testing assumptions: The Shapiro-Wilk test and Levene's test. . Proper reporting of the independent-samples t test. . t, degrees of freedom, and t value. . Probability value. . Effect size. · Toggle Drawer Questions to Consider As you prepare to complete this assessment, you may want to think about other related issues to deepen your understanding or broaden your viewpoint. You are encouraged to consider the questions below and discuss them with a fellow learner, a work associate, an interested friend, or a member of your professional community. Note that these questions are for your own development and exploration and do not need to be completed or submitted as part of your assessment. SHOW LESS Various Forms of the t Test . In w ...

PSYC 355 Inspiring Innovation/tutorialrank.com

jonhson158

Maryland psyc 355 week 2 spss homework 2 new

uopassignment

OutputUniversity of the Philippines-Los Banos, De La Salle University-Manila, Cavite State University

Maryland psyc 355 week 2 spss homework 2 new

merlincarterr

Psyc 355 Massive Success - snaptutorial.com

Reynolds46

Exam 1 Psych 355 3. A p level of 0.05 corresponds to a confidence level of __________% 4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an: 7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation? 8. The paired-samples t test has three assumptions, including all but:

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