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Very Short Guide to Stats for SGR

Very Short Guide to Stats for SGR. Basics of aggregate and statistical data. Inferential v. Descriptive. Descriptive statistics “describe” the data of a sample or population. They are usually aggregate data Average (Mean) GPA Standard Deviation of SAT score

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Very Short Guide to Stats for SGR

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  1. Very Short Guide to Stats for SGR Basics of aggregate and statistical data

  2. Inferential v. Descriptive • Descriptive statistics “describe” the data of a sample or population. They are usually aggregate data • Average (Mean) GPA • Standard Deviation of SAT score • Inferential statistics “infer” (i.e. conclude) relationships between a sample AND a population, or “infer” past, present or future results of a sample/population based on its data. • Regression/correlation analysis of GPA and SAT (relationship between SAT and GPA, and SAT can be used to predict GPA)

  3. Population v. Sample • In inferential statistics, you would refer to the number of participants in your survey as N. If it is a sample or part of a whole, it is n (lowercase), and if it is a total population, it is N (uppercase). • Population: N = 4,432 • Sample: n = 100 • In descriptive studies and descriptive statistics, it is common to refer to participants as N, subgroups of those participants as n • Of the total students surveyed (N = 100), only 10% (n = 10) were male. • For the SGR, you would refer to then the participants as N since this is a descriptive study.

  4. Descriptive Stats 101 • Central Tendency measures common “middles” • Mean is the arithmetic average of items or values • Mode is the most occurring item or value • Median is the item or value of which 50% are greater and 50% are less. • Sometimes GPA or time can be used as a measure, but another measure is one of attitudes and beliefs using a Likert-type scale. • Standard Deviation is a measure of the spread of items or values in a series. Understanding the variation can help you see how close a particular item or value is to other numbers. • Distribution (Histogram) is a visual representation of the number of a particular result in an array of numbers. In this series (number of hours I played WoW over break):8, 0, 0, 3, 2, 10, 0 • Mean = 3.29, Mode = 0, Median = 2, SD = 4.11 In this series (number of hours I worked this week):8, 8, 8, 8, 6, 6, 5 • Mean = 7, Mode = 8, Median = 8, SD = 1.29

  5. Using Excel to do your stats • Mean { =average(range) } • You can compute mode { =mode(range) } or median {=median(range) }, but they might not be as useful in this project. • Standard Deviation { =stdev(range) } • You can also count the number of instances of a value including instances of text: { =countif(range,”value”) } • The following example would count every instance of “male” in the range: =countif(A2:A7,”male”) • You can create frequency distribution histograms by using Tools -> Data Analysis, then Historgram. Histograms count the number of instances of a result in a given array. You can also find these commands by using Insert -> Function. There are also far more complex inferential statistics available in Excel • You can do a complete Descriptive Stats Summary by selecting Tools > Data Analysis (If you don’t see a Data Analysis, then (Excel 2003) Tools > Add-ins > Analysis ToolPak; (Excel 2007) Excel Options > Add-ins > Manage Add-ins > Analysis ToolPak

  6. Writing Stats in APA • Standard Deviation = SD • Mean = M • Descriptive statistics are often written in parentheses after an item that the statistic refers to, and symbols and numbers should be separated by a space • In a survey of DU students, participants (N = 100) responded that money was more important (M = 4.2, SD = .9) than experience (M = 3.5, SD = .76) in selecting a summer job. • In a survey of computer game addicts, females (n = 15) were more likely to be depressed during withdrawal (M = 5.2, SD = .45) than males were (n = 78, M = 3.2, SD = .98) • If unsure about how to write a statistic in your SGR, you can consult the APA Manual (in the library), ask me, or visit http://www.docstyles.com/apa17.htm

  7. Charts and Graphs • Pie graphs – good for showing distributions of a total population (you will have to compute aggregates first) • Line graphs – good for showing time-based, linear progression • Column/Bar graphs – good for showing distribution of individual responses (you will have to create aggregates first) • Y-Axis (vertical) for variables, X-Axis (horizontal) for participants.

  8. Exercise • Perform countif function on gender and major (you will have to create an area for your results that lists the gender/major options). This is just practice doing these two functions and you don’t have to relate them to the next steps. • Pick two or more variables to compare and write a paragraph in APA style using appropriate symbols (M, SD, N, n ) about the data. • Create a graph of some variable or detail of the data, labeling the legend and series items.

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