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HCS 500

HCS 500. Graduate Research Methods. OVERVIEW. Original research Basic stat concepts Types of data Making pictures from numbers. ORIGINAL RESEARCH. You are moving from being a consumer of knowledge to a producer of knowledge.

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HCS 500

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  1. HCS 500 Graduate Research Methods

  2. OVERVIEW • Original research • Basic stat concepts • Types of data • Making pictures from numbers

  3. ORIGINAL RESEARCH • You are moving from being a consumer of knowledge to a producer of knowledge. • There’s a difference between academic research and popular media. You are no longer making book reports or using lexis. A literature review sets up research but isn’t itself research. You need ORIGINAL DATA to be a producer of knowledge. • Popular media ----- textbooks ------ scholarly journals • Your lit review should let you set up a good study. Find what’s relevant, don’t pad footnotes. • There are standards for doing original research. If you do it right, it’s the most important type of work you can do. If you do it wrong, it can be dangerously misleading. • Some things are set in stone; some are up for grabs. If it’s up for grabs, that means you REALLY need to know what you’re doing, not that it doesn’t matter. I will, however, focus on what’s necessary for publication.

  4. DO NOT FEAR THE STAT • Stats aren’t all that hard; we’ll only need basic algebra. If you can read a table and use a spread sheet you’re there. • We’ll be skipping the proofs. • None of this is individually very hard, the hard part is getting all 50 simple things to work right at the same time.

  5. BASIC ALGEBRA • FRACTIONS: If the numerator goes up, the value of the number goes up. If the numerator goes down, the value of the number goes down. Example: • 1/4 3/4 • If the denominator goes up, the value of the number goes DOWN. If the denominator goes down, the value of the number goes up. Example: • 5/8 5/6 5/4

  6. TYPES OF DATA • There are 4 types of data (nominal, ordinal, interval, and ratio), but most statistics really only use 2: categorical (nominal, counting), and interval (continuous, scale). You figure out which statistic to use based on the (a) number of variables, (b) whether there are covariates involved, and (c) the type of data you are working with (categorical or continuous). • TEAM WIN LOSS PCT GAMES BACK • Mets 100 62 .617 --- • Braves 90 72 .555 10 • Yankees 81 81 .500 19 • Cubs 40 122 .247 60 • Note that the Team name is nominal, the place of the teams (1st, 2nd, 3rd, etc.) is ordinal, the number of wins is interval, and the percentage is ratio. Also note the Cubs are in last.

  7. MORE ON TYPES OF DATA • Note also that you can always break ordinal or interval data into categories. You can’t make categorical data interval. • In social science research, ordinal data is often treated as if it is interval, and lots of interval data is only assumed to be interval (on the use of scales, etc.). • Note that with interval data you usually compute an average, and with categorical data you can compute a percentage. The average number of wins = (100 + 90 + 81 + 40)/4, = 77.75. The win percentages are calculated using percentages, so the Mets win percentage = 100/162, = .617

  8. THINGS TO DO WITH NOMINAL DATA • If you have a variable with nominal categories and a single dependent variable, you can make a bar chart.

  9. NOMINAL DATA • If you have a variable nominal categories and a nominal dependent variable, you can make a pie chart for each level of the nominal variable

  10. CONTINUOUS DATA • If you have 2 variables and they are each continuous, you can make a plot.

  11. MORE WORK STUFF • If you have different groups and 2 continuous variables, you can make a plot with separate lines for each group.

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