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Sociology (4,081)
SOC222H5 (93)
Lecture

lecture two

14 Pages
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Department
Sociology
Course Code
SOC222H5
Professor
John Kervin

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Description
SOC 222 -- MEASURING the SOCIAL WORLD TABLES -- Session #2 WHERE WE ARE Ratio is quantitative and all other categories are category **Today variables will either be nominal or ordinal • Will have to variables, like male or female Today’s Objectives: Know… 1. The difference between causation and correlation 2. Three criteria for causation 3. Importance of the three types of bivariate relationships 4. The two kinds of statistics and two key questions in statistics 5. Difference between a percentage and a proportion 6. How to produce a bar chart in SPSS 7. Measures of central tendency for category variables 8. How to produce a crosstabulation in SPSS 9. How to percentage tables 10. How to produce a bivariate clustered bar chart Terms to Know independent variable dependent variable covariation descriptive statistics inferential statistics representative sample frequency distribution central tendency mode median crosstab effect size BIVARIATE RELATIONSHIPS xy- how we indicate this x causes y Dependent and Independent Variables Dependent vs. independent variable- depends, wearing them is effect of aging Causation and Correlation If we find that there’s correlation between poverty and internet use can we determine internet use causes poverty? No! Criteria: to say that x causes y 1. Time Order: X must come before Y in time, that’s why sex is a determinant, if males make more money, you would say earnings determine sex 2.Covariation: X changes, Y changes what ever happens is systematic. One variable varies with another variable, what stats focuses on 3. Non-spurious: does X vary systematically with Y, Three Types of Bivariate Relationships **Category and ratio variables DV IV: Cat Rat Cat Cat  Cat Cat  Rat Rat Rat  Cat Rat  Rat • There are 4 possible types • Catrat, important but not for us, basis of experimental designs • Ratrat- that’s us, what we will look at, regression analysis- procedure that dominates sociology today • Importance of Each Type: The Two Key Questions Two things can get in the way of showing there’s co-variation Descriptive : is there a relationship? How strong is it? And what direction does it take? How strong is relationship between x and y Inferential : if we base conclusion about co-variation on sample and then want to draw on sample…..sample mean we don’t get info from every possible source. always possibility that the sample is bad and doesn’t capture the whole population. Only applies when we have a sample, and asks how accurate it is if we base it on our sample representative sample CATEGORY VARIABLES Frequency Distributions Not so usefull for ratio variables, too many pages and numbers • Tell us what categories there are, what percentage of people are in each category • Percentage is out of 100, counts of things are sometimes hard to understand Percentage and Proportion • Proportions are same thing but instead you just take number and divide it by 100 SPSS Frequency Distributions • Give us counts and percentages Department Cumulative Frequency Percent Valid Percent Percent Valid Chem Eng 29 10.2 10.2 10.2 Elec and Comp Eng 47 16.5 16.5 26.8 East Asian Studies 39 13.7 13.7 40.5 English 20 7.0 7.0 47.5 Microbiology 63 22.2 22.2 69.7 Botany 19 6.7 6.7 76.4 Geography 11 3.9 3.9 80.3 Economics 38 13.4 13.4 93.7 Sociology 18 6.3 6.3 100.0 Total 284 100.0 100.0 The table shows: • Bar Charts SPSS Bar Charts • Best graph is a bar chart for category variables • SPSS Bar Charts Open data set Click on “Graphs” on menu bar Choose “Chart Builder” from dropdown menu This opens the “Chart Builder” procedure box • Top left: list of your variables • Next to it: a white working area • Bottom: • A “Choose from” box. AKA “the gallery” • On top of this box: four selection buttons • Underneath: the five action buttons Steps: 1. Decide which general type of graphic you want (left side of “Choose from” box) 2. Within that general type, pick the specific type (icons – will show name of type) • Simple bar chart is on the left 3. Drag icon up to white working area • This shows a sample of what you’ll get, with some spaces to fill in to complete your chart 4. Drag your category variable into the X-axis area • X-axis will show variable label • Vertical Y-axis will show “Count” 5. Click “OK” • The bar chart will show up in your output window. (Name of procedure will be “GGraph”) If you want to see percentages instead of counts: • Open the “Element Properties” box (if it’s not already open) • Edit Properties: Bar 1 • In “Statistics” area, under “Statistic”, pick “Percentage” on drop-down menu • Ignore the question mark (since you’re percentaging on the total) • Click “Apply”, then “Close” • Result: exactly the same appearance, but percentages i/o counts Central Tendency: Category Variables Nominal Variables • Mode: the category with the highest frequency Department Cumulative Frequency Percent Valid Percent Percent Valid Chem Eng 29 10.2 10.2 10.2 Elec and Comp Eng 47 16.5 16.5 26.8 East Asian Studies 39 13.7 13.7 40.5 English 20 7.0 7.0 47.5 Microbiology 63 22.2 22.2 69.7 Botany 19 6.7 6.7 76.4 Geography 11 3.9 3.9 80.3 Economics 38 13.4 13.4 93.7 Sociology 18 6.3 6.3 100.0 Total 284 100.0 100.0 Ordinal Variables Median: The category containing the case in the middle of the frequency distribution Right major = good job Cumulative
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