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January 21, 2009 I. Types of samples a. Random b. Systematic c. Stratified d. Convenience e. Probability f. Cluster g. Judgment h. Simple Random Sample II. Good Techniques a. Random b. Systematic c. Cluster d. Stratified e. Simple Random III. Ok Technique a. Probability IV.Bad Technique a. Convenience b. Judgment V. Stratified Example a. Sorting people according to some characteristic and randomly select from each subgroup i. EX: Male/ Female

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VI.Systematic a. Choose every 10 th , 20 th , ect. … and randomly pick when to start b. Problem: i. If they have data with any type of cycle then data has flaws VII. Simple Random Sample a. Type of Probability sample b. Every item has same probability of being selected i. EX: pull a number out of a hat VIII. Internet Samples a. Problems: i. Potential population only has access to internet ii. People can choose whether or not to respond IX.Focus Groups a. Good way to help build a survey X. Statistical graphs a. Why graph i. Organize data ii. Condense data iii. Display data

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Unformatted text preview: iv. Reveal meaning in date v. Sometimes only way to illustrate fundamental differences in data b. Steps i. What type of data ii. Order c. Types of graphs i. Qualitative data – always way to illustrate frequency 1. Bar/ column a. Axes i. Category & frequency 2. Pareto chart 3. Pie chart a. Only one that doesn’t have axes 4. Example a. Pareto diagram i. Highest frequency on left b. Qualitative data c. There’s space between columns d. Left most has more than twice the # of observations than the 2 nd most e. Used to show biggest problem/ error ii. Quantitative Data 1. Histogram 2. Stem & Leaf 3. Frequency Poly god 4. Ogive a. Cumulative frequency b. Adds current & previous frequencies 5. Axes: a. Classes & frequencies 6. Example: a. Bins i. Single # representative of the class mark – AKA midpoint b. Continuity c. Bimodal d. Range 9-36 e. Mixed data?...
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