Fluent Essays

SOCW 6311 wk 4 assignment Submit a 1-page paper of the following: An analysis of the relationship between study design and statistical analysis used in the case study that includes: An explanation of why you think that the agency created a plan to evaluate the program An explanation of why the social work agency in the case study chose to use a chi square statistic to evaluate whether there is a difference between those who participated in the program and those who did not (Hint: Think about the level of measurement of the variables) A description of the research design in terms of observations (O) and interventions (X) for each group. Interpret the chi-square output data. What do the data say about the program? Full intext citation and full references APA 7th addition  (refence for this APA provided)Statistics for Social Workers J. Timothy Stocks tatrstrrsrefers to a branch ot mathematics dealing th the direct de<erip- tion of sample or population characteristics and the an.ll)5i• of popula· lion characteri>tics b) inference from samples. It co•·ers J wide range of content, including th~ collection, organization, and interpretJtion of data. It is divided into two broad categoric>: de;cnptive >lathrics and inferential >lJt ost ics. Descriptive statistics involves the CQnlputation of statistics or pnr.1meters to describe a sample or a popu lation _~ All t he data arc available and used in <.omputntlon o f t hese aggregate characteristics. T his may involve reports of central tendency or v.~r i al>il i ty of single variables (univariate statistics). ll also may involve enumeration of the ICiation- sh ips between or among two or moo·e variables (bivariate or multivariJte stot istics}. Descriptiw statistics arc used 10 provide information about a large m.b> of data in a form that ma) be easily understood. The defining characteristic of descriptive ;tJtistks b that the product is a report, not .on inference. Inferential statisti<> imolvc the construction of a probable description of the charac· teristics of a population b•sed on s.unple data. We compute statistics from .1 pJrtial;et of the population data (a samplt) to estimate the population parameters. Thrse t<timates are not exact, but \\·e can mo~k..: reawnable judgments as w ho\V preruc our c~lim:ues are. Included within inferential statiwcs i;, hypothesis testing, a procedure for U>ing mathe- m:uics tO provide evidence for the exi<tence of relationships between o r among variable;. T bis testing is a form of inferential •l~umem. Descriptive Statistics Measures of Central Tendency Measures of central tenden) are individual numbers that typify the tot.tl set of ~cores. The three most frequently used mca>urcs of centraltendenq are the arithmetic mean, the mode, and the median. Arir!Jmeric .\1ea11. The arithmetic mean usually is simply called the mca11. It also is called the m-erage. It is computed b) adding up all of a set of scores and dwidmg by the number of scores in the set. The algebraic representation of this is 75 76 PA11 f I • OuANTifAllVi AffkOAGHU: fouHo~;noM Of Ot.r CO ltf(TIOJ ~, =l:: X , 11 where 11 represents the popu I at ion mean, X represems an individual score, and rr is t he number of scores being adde(l. The formula for the sample mean is the same except t hat the mean is represented by the variable lener with a bar above it: - l:;X X= --. II Following are t he numbers of class periods skipped by 20 seventh-graders d uring I week: {1, 6,2,6, 15,2(),3,20, 17, 11, 15, 18,8,3, 17, 16, 14, 17,0, 101. Wecomputethe mean by adding up the class periods missed and dh•iding by 20: l:;X 219 • J.l = -- = - = 10.9o. II 20 Mode. The mode is the most frequently appearing score. It really is not so much a meas© 2014 Laureate Education, Inc. Page 1 of 5 Week 4: A Short Course in Statistics Handout This information was prepared to call your attention to some basic concepts underlying statistical procedures and to illustrate what types of research questions can be addressed by different statistical tests. You may not fully understand these tests without further study. However, you are strongly encouraged to note distinctions related to type of measurement used in gathering data and the choice of statistical tests. Feel free to post questions in the “Contact the Instructor” section of the course. Statistical symbols: µ mu (population mean) α alpha (degree of error acceptable for incorrectly rejecting the null hypothesis, probability that results are unlikely to occur by chance) ≠ (not equal) ≥ (greater than or equal to) ≤ less than or equal to) ᴦ (sample correlation) ρ rho (population correlation) t r (t score) z (standard score based on standard deviation) χ 2 Chi square (statistical test for variables that are not interval or ratio scale, (i.e. nominal or ordinal)) p (probability that results are due to chance) Descriptives: Descriptives are statistical tests that summarize a data set. They include calculations of measures of central tendency (mean, median, and mode), and dispersion (e.g., standard deviation and range). Note: The measures of central tendency depend on the measurement level of the variable (nominal, ordinal, interval, or ratio). If you do not recall the definitions for these levels of measurement, see http://www.ats.ucla.edu/stat/mult_pkg/whatstat/nominal_ordinal_interval.htm You can only calculate a mean and standard deviation for interval or ratio scale variables. For nominal or ordinal variables, you can examine the frequency of responses. For example, you can calculate the percentage of participants who are male and female; or the percentage of survey respondents who are in favor, against, or undecided. Often nominal data is recorded with numbers, e.g. male=1, female=2. Sometimes people are tempted to calculate a mean using these coding numbers. But that would be http://www.ats.ucla.edu/stat/mult_pkg/whatstat/nominal_ordinal_interval.htm © 2014 Laureate Education, Inc. Page 2 of 5 meaningless. Many questionnaires (even course evaluations) use a likert scale to represent attitudes along a continuum (e.g. Strongly like … Strongly dislike). These too are often assigned a number for data entry, e.g. 1–5. Suppose that most of the responses were in the middle of a scale (3 on a scale of 1–5). A researcher could observe that the mode is 3, but it would not be reasonable to say that the average (mean) is 3 unless there were exact differences between 1 and 2, 2 and 3 etc. The numbers on a scale such as this are ordered from low to high or high to low, but there is no way to say that there is a quantifiably equal difference between each of the choices. Week 4 Handout: Chi-Square Findings The chi square test for independence is used to determine whether there is a relationship between the two variables that are categorical in the level of measurement. In this case, the variables are: employment level and treatment condition. It tests whether there is a difference between groups. The research question for the study is: Is there a relationship between the independent variable, treatment, and the dependent variable, employment level? In other words, is there a difference in the number of participants who are not employed, employed part-time and employed full-time in the program and the control group (i.e., waitlist group)? The hypotheses are: H0 (The null hypothesis): There is no difference in the proportions of individuals in the three employment categories between the treatment group and the waitlist group. In other words, the frequency distribution for variable 2 (employment) has the same proportions for both categories of variable 1 (program participation). ** It is the null hypothesis that is actually tested by the statistic. A chi square statistic that is found to be statistically significant, (e.g. p< .05) indicates that we can reject the null hypothesis (understanding that there is less than a 5\% chance that the relationship between the variables is due to chance). H1 (The alternative hypothesis): There is a difference in the proportions of individuals in the three employment categories between the treatment group and the waitlist group. ** The alternative hypothesis states that there is a difference. It would allow us to say that it appears that the treatment (voc rehab program) is effective in increasing the employment status of participants. Assume that the data has been collected to answer the above research question. Someone has entered the data into SPSS. A chi-square test was conducted, and you were given the following SPSS output data:Statistics for Social Workers J. Timothy Stocks tatrstrrsrefers to a branch ot mathematics dealing th the direct de<erip- tion of sample or population characteristics and the an.ll)5i• of popula· lion characteri>tics b) inference from samples. It co•·ers J wide range of content, including th~ collection, organization, and interpretJtion of data. It is divided into two broad categoric>: de;cnptive >lathrics and inferential >lJt ost ics. Descriptive statistics involves the CQnlputation of statistics or pnr.1meters to describe a sample or a popu lation _~ All t he data arc available and used in <.omputntlon o f t hese aggregate characteristics. T his may involve reports of central tendency or v.~r i al>il i ty of single variables (univariate statistics). ll also may involve enumeration of the ICiation- sh ips between or among two or moo·e variables (bivariate or multivariJte stot istics}. Descriptiw statistics arc used 10 provide information about a large m.b> of data in a form that ma) be easily understood. The defining characteristic of descriptive ;tJtistks b that the product is a report, not .on inference. Inferential statisti<> imolvc the construction of a probable description of the charac· teristics of a population b•sed on s.unple data. We compute statistics from .1 pJrtial;et of the population data (a samplt) to estimate the population parameters. Thrse t<timates are not exact, but \\·e can mo~k..: reawnable judgments as w ho\V preruc our c~lim:ues are. Included within inferential statiwcs i;, hypothesis testing, a procedure for U>ing mathe- m:uics tO provide evidence for the exi<tence of relationships between o r among variable;. T bis testing is a form of inferential •l~umem. Descriptive Statistics Measures of Central Tendency Measures of central tenden) are individual numbers that typify the tot.tl set of ~cores. The three most frequently used mca>urcs of centraltendenq are the arithmetic mean, the mode, and the median. Arir!Jmeric .\1ea11. The arithmetic mean usually is simply called the mca11. It also is called the m-erage. It is computed b) adding up all of a set of scores and dwidmg by the number of scores in the set. The algebraic representation of this is 75 76 PA11 f I • OuANTifAllVi AffkOAGHU: fouHo~;noM Of Ot.r CO ltf(TIOJ ~, =l:: X , 11 where 11 represents the popu I at ion mean, X represems an individual score, and rr is t he number of scores being adde(l. The formula for the sample mean is the same except t hat the mean is represented by the variable lener with a bar above it: - l:;X X= --. II Following are t he numbers of class periods skipped by 20 seventh-graders d uring I week: {1, 6,2,6, 15,2(),3,20, 17, 11, 15, 18,8,3, 17, 16, 14, 17,0, 101. Wecomputethe mean by adding up the class periods missed and dh•iding by 20: l:;X 219 • J.l = -- = - = 10.9o. II 20 Mode. The mode is the most frequently appearing score. It really is not so much a meas1 Title of the Paper in Full Student Name Program Name or Degree Name (e.g., Master of Science in Nursing), Walden University COURSE XX: Title of Course Instructor Name Month XX, 202X Abstract AAA bbb cccc dddd eeee ffff gggg hhhh iiii jjjj kkkk llll mmmm nnnn oooo pppp qqqq rrrr sssss tttt uuuu vvvv wwww xxxx yyyy zzzz. AAA bbb cccc dddd eeee ffff gggg hhhh iiii jjjj kkkk llll mmmm nnnn oooo pppp qqqq rrrr sssss tttt uuuu vvvv wwww xxxx yyyy zzzz. AAA bbb cccc dddd eeee ffff gggg hhhh iiii jjjj kkkk llll mmmm nnnn oooo pppp qqqq rrrr sssss tttt uuuu vvvv wwww xxxx yyyy zzzz. AAA bbb cccc dddd eeee ffff gggg hhhh iiii jjjj kkkk llll mmmm nnnn oooo pppp qqqq rrrr sssss tttt uuuu vvvv wwww xxxx yyyy zzzz. Title of the Paper in Full AAA bbb cccc dddd eeee ffff gggg hhhh iiii jjjj kkkk llll mmmm nnnn oooo pppp qqqq rrrr sssss tttt uuuu vvvv wwww xxxx yyyy zzzz. 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