Details in the Social Science Paper

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1. Quantitative Research - focuses on measurement and analysis of casual relationships
1. Kinds
1. Statistics
1. General Remarks
1. Help overcome vague statements
2. Provide reproducible information
3. Give some idea of range of error
2. Techniques
1. Sampling
1. Small samples from a population can be used to give information on the population
1. Mean -average
2. Standard Deviation - average difference from the mean
3. Error - What is the confidence in the numbers (e.g.. +/- 5%)
2. Need for proper techniques
1. Is everyone equally likely to be included?
1. Does everyone have a telephone?
2. Is everyone likely of be home when called?
3. Does the survey rely on people returning the survey?
2. Is the survey biased?
1. Are there loaded questions?
2. Are the questions clear?
3. Are the questions worded so that people don't know what answer is "expected"?
3. How are the results analyzed?
1. Are both favorable and unfavorable results reported?
2. Are results reported objectively?
3. Does the discussion of the results match the results?
3. In some cases, a control and experimental group is needed. (e.g.. testing new drugs.)
1. Control Group - receives no action
2. Experimental Group - receives action
2. Measuring
1. Scales
1. Ratios
2. Percentages
3. Nominal - named by group (i.e.. type of car)
4. Analysis - continuous variables (i.e.. speed, weight)
2. Type on Analysis See Statistics Page
1. General
1. Mean -average
2. Standard Deviation - average difference from mean
3. Confidence Interval - at what range are we, say 90% sure that the results are correct.
4. Error - what is the margin of error (i.e.. +/- 5%)
2. More Advanced
1. Regression Analysis - measure the relationship of two or more variable on each other (e.g.. height vs. weight)
2. T-test - measures whether there is a significant difference between two samples. There are a number of extensions to this concept to include additional variables. These come under ANOVA (ANalysis Of VARiance)
3. Presentation - Graphs, Tables and Charts
1. Tables
1. Used to present data that was collected. The most basic form of presentation, but on that gives the most raw data to the reader.
2. Graphs
1. Used to present data in a organized manner, usually to highlight a point
2. Types (These are available in most Word Processing and Spreadsheet packages)
1. Bar
2. Pie
3. Line
4. Stacked Bar
5. Area
6.  Scatter
7. Flow Models
8. Bell Curve - Normal Distribution Curve
9. Others
3. Charts
1. Used to show major points in highlighted form
2. Also available in most Word Processors
4. Things to lookout For
1. Confidence Level - based on the sample size and distribution of results
1. The more observation, the higher the confidence
2. The less distribution about the mean, the high the confidence
3. Must be calculated
1. Usually presented as "90% confidence that the mean is within certain limits"
2. Regression correlation (R-square)
1. 1 = perfect correlation
2. 0 = no correlation
3. -1 = perfect negative correlation
4. R-squared represents the percentage of the variation between two variables that is explained by a regression line. Numbers near 1 or -1 indicate that the regression line, the line though the points, explains most of the differences. A value near 0 indicated that the line explains nothing.
2. Qualitative Research - focuses in interpretive approach
1. Examples
1. Ethnography - Study of cultures though observation
2. Interviews
3. Examples
4. Focus Groups
5. Case Studies
2. Analysis
1. Conclusions drawn from observations
2. Much of the analysis depends on the writer's ability to form a logical argument.