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Sociology 400 Review. Prepared by Sarah Perry Johnson. Review of Levels of Measurement. The 4 Levels of Measurement are: Nominal Ordinal Interval Ratio The subsequent slides will allow us to revisit each level of measurement and review the characteristics of each variable.

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## Sociology 400 Review

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**Sociology 400 Review**Prepared by Sarah Perry Johnson**Review of Levels of Measurement**• The 4 Levels of Measurement are: • Nominal • Ordinal • Interval • Ratio • The subsequent slides will allow us to revisit each level of measurement and review the characteristics of each variable.**Nominal Variable**• Nominal (nom=name) • Qualitative • No numerical value • Discreet • Examples: religion, nationality, occupation, etc. • Nominal variables are also considered to be categorical.**Ordinal Variables**• Ordinal (order) • Quantitative • In order of cases greater than or less than; a range • Discreet • Examples: level of conflict (low to high), socioeconomic status (SES), Starbucks sizes, educational attainment, etc.**Interval Variables**• Interval • Quantitative • Numerical/integer value; no absolute/fixed “0” point • Continuous • Example: temperature, depression score (starts at 6, ends at 60)**Ratio Variables**• Ratio • Quantitative • Numerical/integer value; has an absolute fixed “zero” point • Continuous • Examples: number of children, number of cigarettes smoked, number of feet/miles, number of votes**Basic Template for Relationships Questions**• Relationships question: Is there a relationship between [the IV] and [the DV]? • Example: Is there a relationship between the number of hours a person studies per day and GPA? • Independent Variable: # of daily study hours • Dependent Variable: Grade Point Average (GPA) • Used for Pearson, Spearman, and Regression Questions**Basic Template for Differences Questions**• Differences question: Is there a difference between [categories of the IV] based on [the DV]? • Is there a difference between the United States, China, and Sweden based on GDP? • Independent Variable: countries (US, China, and Sweden) • Dependent Variable: Gross Domestic Product (GDP score) • Used for Chi-Square, T-Test, and ANOVA Questions**Six Types of Tests:**Charts and Templates**Chi-Square Test:Variables and Reporting**Chi-Square Test • Independent Variable: Discreet • Dependent Variable: Discreet Report template • Is there is a difference between [categories of the IV] based on the [DV]? • There is a difference between [categories of the IV] based on the [DV] (chi-square[χ²=?], p-value[p=?]).**T-Test:Variables and Reporting**T-Test • Independent Variable: Discreet (limit: 2 categories) • Dependent Variable: Continuous Report template • Is there is a difference between [categories of the IV] based on the [DV]? • There is a difference between [categories of the IV] based on the [DV] (t-score[t=?], p-value[p=?]). • State which category of the IV has more...[Cat 1 has around __% more than Cat 2.]**ANOVA:Variables and Reporting**ANOVA • Independent Variable: Discreet (2 or more categories) • Dependent Variable: Continuous Report Template • Is there is a difference between [2+ categories of the IV] based on the [DV]? • There is a difference between [2+ categories of the IV] based on the [DV] (F-score[F=?], p-value[p=?]). • State which category of the IV has the most and the least [Cat 1 has the most and Cat 2 has the least. There is no significant difference between Cat 3, however, the difference between Cat 1 and Cat 2 were significant.]**Pearson Correlation:Variables and Reporting**Pearson Correlation • Independent Variable: Continuous • Dependent Variable: Continuous Report Template • Is there is a relationship between [the IV] and [the DV]? • There is a relationship between [the IV] and [the DV] (r-score[r=?], p-value [p=?]). • State the strength and direction: This is a [state strength], [state direction] relationship. • State the R² (square the r value): [The IV] explains about __% of the variance in [the DV].**Spearman Correlation:Variables and Reporting**Spearman Correlation • Independent Variable: Ordinal • Dependent Variable: Ordinal Report Template • Is there a relationship between [the IV] and [the DV]? • There is a relationship between [the IV] and [the DV] (rs-score[ rs=?], p-value [p=?]). • State the strength and direction: This is a [state strength], [state direction] relationship. • No R-square: ordinal variables**Regression:Variables and Reporting**Regression • Independent Variable: Continuous • Dependent Variable: Continuous**Regression:Variables and Reporting (cont.)**• Is there a relationship between [the IV] and [the DV]? • There is a relationship between [the IV] and [the DV] (p-value[p=?]). • State the strength and direction: This is a [state strength], [state direction] relationship.**Regression:Variables and Reporting (cont.)**• State the slope: For each additional [1 unit of the IV] of the [units of analysis], the [DV] is expected to [increase/decrease] by [# units of the DV]. • State the R² (square the r value): [The IV] explains about __% of the variance in [the DV]. • State the y-intercept: In the case that [the IV] is 0, it is predicted that [the DV] will be [amount and units of measurement]. • Or: A [unit of analysis] that is [units of measurement of IV] is predicted to be [amount and units of measurement of DV]**Multiple Regression:Variables and Reporting**Multiple Regression • Independent Variable: Continuous (2+) • Dependent Variable: Continuous Report Template: • Is there a relationship between [IV#1], [IV#2], and [IV#3] with [the DV]? • State the Adjusted R2: [IV#1], [IV#2], and [IV#3] together explain about [___%] of the variance in [the DV].**Multiple Regression:Variables and Reporting (cont.)**• Report on the Adjusted R²: [IV#1, IV#2, and IV#3] together explain about __% of the variance in [the DV]. • Next, state the slope for each IV with the DV. • Hint: if you have three IV’s, you should write three separate statements: IV#1/DV, IV#2/DV, and IV#3/DV. (see next slide…)**Multiple Regression:Variables and Reporting (cont.)**• For each additional [1 unit of the IV#1] of the [units of analysis], the [DV] is expected to [increase/decrease] by [# units of the DV], holding constant for [IV#2] and [IV#3] (p=). • For each additional [1 unit of the IV#2] of the [units of analysis], the [DV] is expected to [increase/decrease] by [# units of the DV], holding constant for [IV#1] and [IV#3] (p=). • For each additional [1 unit of the IV#3] of the [units of analysis], the [DV] is expected to [increase/decrease] by [# units of the DV], holding constant for [IV#1] and [IV#2] (p=).**Multiple Regression:Variables and Reporting (cont.)**• Each time you report on a slope, add to the end of the statement “holding constant for” and list the leftover variables. • For example: For each additional [1 unit of the IV#1] of the [units of analysis], the [DV] is expected to [increase/decrease] by [# units of the DV], holding constant for [IV#2 and IV#3] (p=). • For the test, regarding the slope, you will only have to report on one of the IV’s paired with the DV.**Example: Pearson correlation-Strength and Direction**Is there a relationship between self-concept scores and depression scores? To determine whether there is a statistically significant relationship between the variables, look at the p-value. To determine the strength and direction of the relationship, look at the r-value.**Strength and Direction(continued)**Strength of the relationship • According to our chart, the integer value 0.852 shows that there is a very high/strong relationship between self-concept scores and depression scores. Direction of the relationship • According to our chart, the negative sign (-) in front of the integer denotes that the relationship is a negative one (as X increases, Y decreases). So how shall we report this data for a Pearson’s Correlation?**Strength and Direction(continued)**Report template for Pearson’s correlation • Is there is a relationship between [the IV] and [the DV]? • There is a difference between [the IV] and [the DV] (r-score[r=?], p-value [p=?]). • State the strength and direction: This is a [state strength], [state direction] relationship. Report: • There is a relationship between self-concept scores and depression scores (r=-0.852; p=0.004). • This is a very strong, negative relationship.**Example: Spearman’s Rho**According to the above Spearman’s rho chart, rs =0.290. Direction: The integer value is positive/negative. Therefore, the direction of the relationship is positive/negative. Strength: According to the strength chart, the value is____________. Therefore, the strength of the relationship is ____________.**Spearman’s Rho(continued)**• Time to report on the value for a Spearman’s rho: • There is a relationship between __________ and __________ (rs=_____;p=_____). This is a ________________ relationship.**Most and Least**• Report on the most and least based on the means report. Variable to Quantify: Jelly beans • Sue: 56 • Jenny: 39 • Carly: 45 • Sue has the most jelly beans and Jenny has the least [amount of jelly beans].**Most and Least(continued)**Let’s evaluate the same type of example from Lab 8. What is the unit of measurement? (Hint-it is contained in the box above the table…) What is the largest value? What is the smallest value?**Most and Least(continued)**Variable to quantify: age Descriptors for least and most in relationship to age • Least=Youngest • Most=Oldest • Perot voters are the youngest and the Clinton voters are the oldest. -Or- • People who voted for Perot are the youngest and people who vote for Clinton are the oldest.

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