{"id":38666,"date":"2024-11-23T20:39:08","date_gmt":"2024-11-23T20:39:08","guid":{"rendered":"https:\/\/www.writemyessays.app\/blog\/questions\/lab-6-producing-bivariate-tables-and-using-measures-of-association-and-chi-square-statistics-to-understand-them\/"},"modified":"2024-11-23T20:39:08","modified_gmt":"2024-11-23T20:39:08","slug":"lab-6-producing-bivariate-tables-and-using-measures-of-association-and-chi-square-statistics-to-understand-them","status":"publish","type":"questions","link":"https:\/\/www.writemyessays.app\/blog\/questions\/lab-6-producing-bivariate-tables-and-using-measures-of-association-and-chi-square-statistics-to-understand-them\/","title":{"rendered":"Lab 6. Producing Bivariate Tables and Using Measures of Association and Chi Square Statistics to Understand Them."},"content":{"rendered":"
<\/div>\n
Question A&b4&5 are done. thats the graphs.<\/div>\n
<\/div>\n
<\/div>\n

Producing Bivariate Tables and Using Measures of Association and Chi Square Statistics to
\nUnderstand Them. Due Dec 4, 2024 by midnight in the lab 6 folder of Blackboard
\nThis lab will introduce you to some more of SPSS\u2019s capabilities for bivariate crosstabulation. The
\nfocus here is on computing and interpreting crosstabulation tables, measures of association and chi
\nsquare statistics. The data set will be the GSS2008_lab6.SAV, the 2008 GENERAL SOCIAL
\nSURVEY DATA set we have been using most of the semester. The data set and the codebook
\n(2008_GSSCODEBOOK.pdf) are in the Lab 6 folder in blackboard. Download them to a lab 6
\nfolder on your computer to complete the assignment, and then move them to the virtual desktop to
\nwork in SPSS. Make sure to create a lab 6 word document to receive your answers. BE SURE TO
\nORGANIZE YOUR ANSWERS USING THE NUMBERING SYSTEM OF THE ASSIGNMENT.
\nUSE FULL SENTENCES TO ANSWER ALL QUESTIONS. There will be penalties for
\ndisorganization. ALL QUESTIONS WEIGHTED EQUALLY. Once the assignment is complete,
\nupload the word document that has your answers to the lab 6 folder in blackboard.
\nPart A.
\nIn part A of this lab, we will look at attitudes about taxes on the rich and their relationship to race.
\nOne of the variables used is TAXRICH1, a measure of people\u2019s attitudes towards taxes on rich
\npeople. The variable is measured by the question \u201cGenerally, how would you describe taxes in
\nAmerica today. We mean all taxes together, including social security, income tax, sales tax, and all
\nthe rest: First, for those with high incomes, are taxes too high, about right or too low\u201d and is located
\non page 464 of the codebook. The second variable is RACE (RACE-white, black or other). Race is
\nlocated on page 316 of the codebook.
\n1) Make a hypothesis for the relationship between TAXRICH1 and RACE. Make TAXRICH1
\nthe dependent variable and RACE the independent variable. Please make a directional
\nhypothesis.
\n2) Provide a theoretical rationale for the hypothesis you made in question 1.
\n3) What are the levels of measurement for the dependent and the independent variables?
\n4) What measures of association are appropriate for assessing the strength of the relationship
\nbetween TAXRICH1 and RACE?
\n5) Follow these instructions to perform the crosstabulation analysis to examine your hypothesis
\na. Click ANALYZE, DESCRIPTIVE STATISTICS, CROSSTABS.
\nb. Select TAXRICH1 from the left column and place in the ROW box as the dependent
\nvariable. NOTE:THE VARIABLE IS TAXRICH1 \u2013 NOT TAXRICH!
\nc. Select RACE from the left column and place it in the COLUMN box as the independent
\nvariable.
\nd. Click on CELLS to open the CROSSTAB CELL DISPLAY and make sure
\nOBSERVED in COUNTS and COLUMN in PERCENTAGES are checked. Click
\nCONTINUE
\n2
\ne. Click STATISTICS and then click LAMDA and PHI AND CRAMER\u2019S V under
\nNOMINAL and CHI \u2013SQUARE. Then click CONTINUE and then OK to obtain
\nresults.
\n6) Copy and paste the CROSSTABULATION table, the CHI SQUARE TEST table, the
\nDIRECTIONAL MEASURES table, and the SYMMETRIC MEASURES table into your lab
\ndocument. If the table is too wide for your page, right-mouse click in the middle of the table
\nand select TABLE PROPERTIES and select CENTER and change the TABLE WIDTH to
\nabout 8 inches.
\n3
\n4
\n7) Discuss the relationship depicted in the crosstabulation table, using selected percentage data to
\nsupport your claims.
\n8) Is the relationship observed in your crosstabulation results a weak, moderate or strong one?
\nReport the LAMBDA (look in the value cell of the DIRECTIONAL MEASURES table \u2013 the
\nattitudes about taxes for the rich dependent) and CRAMER\u2019S V (look in the value cell of the
\nSYMMETRIC MEASURES table for Cramer\u2019s V) produced by SPSS to defend your answer.
\nRemember that a value of Lambda and Cramer\u2019s V between 0-0.3 means weak relationship,
\n0.3 to 0.5 is moderate and 0.5+ is strong.
\n9) Is the relationship depicted in the crosstabs statistically significant or not? Look in the chi
\nsquare test table for the relevant information. Report the value of the PEARSON CHI
\nSQUARE, the DEGREES OF FREEDOM(DF) and the probability associated with the chi
\nsquare(look in THE ASYMPTOTIC SIGNIFICANCE CELL OF THE PEARSON CHI
\nSQUARE for this probability). Remember that when this probability is less than or equal to
\n.05, the relationship observed in the crosstab is statistically significant. You must then reject
\nthe null hypothesis of no relationship in the population between your dependent and
\nindependent variables, and be left with the alternative hypothesis that there is a relationship
\nbetween the two variables in the population. However, if the probability associated with the
\nchi square statistic is larger than 0.05, then the relationship is statistically nonsignificant,
\nmeaning that the relationship is likely due to random chance and you cannot reject the null
\nhypothesis of no relationship in the population.
\n10) Is the relationship observed in the crosstabulation table consistent or not consistent with
\nyour hypothesis? If you cannot reject the null hypothesis of no relationship then you have to
\nconclude that the relationship observed in the crosstabulation table is not consistent with your
\nhypothesis, unless you made a null hypothesis, which is not usually done. However, if you can
\nreject the null hypothesis, you may still conclude that the relationship is not consistent with
\nyour hypothesis. You have to compare the relationship observed in the crosstabulation table
\nwith the hypothesis you made to decide whether the former is consistent or not consistent with
\nthe latter. Please explain your answer in detail.
\nPart B
\nIn this part we will look at the relationship between attitudes towards capital punishment and race.
\nThe two variables to be used are CAPPUN \u201cDo you favor or oppose the death penalty for persons
\nconvicted of murder?\u201d on page 28 of the codebook and RACE (white, black, other). Inspect the two
\nvariables in the codebook to make sure you understand them and then answer the following
\nquestions.
\n1) Make a hypothesis involving CAPPUN and RACE. Treat CAPPUN as the dependent variable
\nand RACE as the independent variable. Again please make a directional hypothesis.
\n5
\n2) Provide a theoretical rationale for the hypothesis you made in question 1.
\n3) What are the levels of measurement for the dependent and the independent variables?
\n4) What measures of association are appropriate for assessing the strength of the relationship
\nbetween CAPPUN and RACE?
\n5) Follow these instructions to perform the crosstabulation analysis
\na. Click ANALYZE, DESCRIPTIVE STATISTICS, CROSSTABS.
\nb. Select CAPPUN from the left column and place in the ROW box as the dependent
\nvariable.
\nc. Select RACE from the left column and place it in the COLUMN box as the independent
\nvariable.
\nd. Click on CELLS to open the CROSSTAB CELL DISPLAY and make sure
\nOBSERVED under COUNTS and COLUMN in PERCENTAGES are checked. Click
\nCONTINUE
\ne. Click STATISTICS and then click LAMDA and CRAMER\u2019s V under NOMINAL and
\nCHI \u2013SQUARE and click CONTINUE. Then click OK to obtain results.
\n6) Copy and paste the crosstabulation table, the chi square test, the directional measures table and
\nthe symmetric measures table into your lab document. If the table is too wide for your page,
\nright-mouse click in the middle of the table and select TABLE PROPERTIES and select
\nCENTER and change the TABLE WIDTH to about 8 inches.
\n7) Discuss the relationship depicted in the crosstabs table, using selected percentage data to
\nsupport your claims.
\n8) Is the relationship observed in your crosstabulation results a weak, moderate or strong one?
\nInspect the LAMBDA and CRAMER\u2019S V produced by SPSS and use them to answer. Be sure
\nto report numbers to support your statements.
\n9) Use the chi-square statistic (PEARSON CHI-SQUARE) and its degrees of freedom (DF) to
\nexamine whether the relationship is statistically significant or not. Is the relationship depicted
\nin the crosstabs statistically significant or not? Look in the chi square test table for the relevant
\ninformation. Report the value of the PEARSON CHI SQUARE, the DEGREES OF
\nFREEDOM(DF) and the probability associated with the chi square(look in THE
\nASYMPTOTIC SIGNIFICANCE CELL OF THE PEARSON CHI SQUARE for this
\nprobability). Remember that when this probability is less than or equal to .05, the relationship
\nobserved in the crosstab is statistically significant. You must reject the null hypothesis of no
\nrelationship between your dependent and independent variables. You will therefore be left
\nwith the alternative hypothesis that there is a relationship between the two variables in the
\npopulation. However, if the probability associated with the chi square statistic is larger than
\n0.05, then the relationship is statistically nonsignificant, meaning that the relationship is likely
\ndue to random chance and you cannot reject the null hypothesis of no relationship in the
\npopulation.
\n10) Is the relationship observed in the crosstabulation table consistent or not consistent with
\nyour hypothesis? If you cannot reject the null hypothesis of no relationship then you have to
\nconclude that the relationship observed in the crosstabulation table is not consistent with your
\nhypothesis, unless you made a null hypothesis, which is not usually done. However, if you can
\n6
\nreject the null hypothesis, you may still conclude that the relationship is not consistent with
\nyour hypothesis. You have to compare the relationship observed in the crosstabulation table
\nwith the hypothesis you made to decide whether the former is consistent or not consistent with
\nthe latter. Explain whatever answer you give.<\/p>\n","protected":false},"excerpt":{"rendered":"

Question A&b4&5 are done. thats the graphs. Producing Bivariate Tables and Using Measures of Association and Chi Square Statistics to Understand Them. Due Dec 4, 2024 by midnight in the lab 6 folder of Blackboard This lab will introduce you to some more of SPSS\u2019s capabilities for bivariate crosstabulation. The focus here is on computing […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":[],"disciplines":[16],"paper_types":[],"tagged":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/questions\/38666"}],"collection":[{"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/questions"}],"about":[{"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/types\/questions"}],"author":[{"embeddable":true,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/comments?post=38666"}],"version-history":[{"count":0,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/questions\/38666\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/media?parent=38666"}],"wp:term":[{"taxonomy":"disciplines","embeddable":true,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/disciplines?post=38666"},{"taxonomy":"paper_types","embeddable":true,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/paper_types?post=38666"},{"taxonomy":"tagged","embeddable":true,"href":"https:\/\/www.writemyessays.app\/blog\/wp-json\/wp\/v2\/tagged?post=38666"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}