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26 Cards in this Set
- Front
- Back
Quantitative Variable
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age, height, weight, temperature
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Qualitative Variable
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Characteristics- gender, religious preferance, geographic location
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Discrete Variables
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Can be counted
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Continuous Variables
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can assume all values between any 2 specific values- obtained by measuring
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Data<qualitative or quantitative
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Quantitative<Discrete or Continuous
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Descriptive Statistics
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collection, organization, summarization, and presentation of data: census-average age, income, or other characteristics of US population
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Inferential Statistics
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make inferences from sample to populations: uses probability-
Generalizing from samples to populations, estimations and hypothesis tests, relationships and predictions |
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Nominal level measurement
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mutually exclusive exhausting categories in which no order or ranking can be imposed on the data: zip code, gender, eye color, political affiliation, major field, nationality
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Ordinal level measurement
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categories that can be ranked: grades, 1st 2nd place, rating scale(poor, good), ranking of tennis players
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Interval level measurement
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ranks data - no zero: SAT score, IQ, Temperature
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Ratio level measurement
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lift twice as much, height weight, time, salary, age
true zero |
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Random Sample
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chance methods, random numbers, table of random numbers
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Systematic Sample
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numbering then selecting everty kth subject
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Stratified Sample
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dividing poplulation into groups then selecting from each group
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Cluster Sample
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intact group representative of the population
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Quasi-experimental study
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intact groups when random assignment is not possible
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Hawthorne Effect
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Participants change behavior because they knew they were being tested
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frequency distribution
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organization of raw data in table form using classes and frequencies
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3 types of frequency distribution
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categorical and grouped and ungrouped
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class midpoint
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X= lower boundary + upper boundary /2
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Histogram
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contigious vertical bars
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Frequency Polygon
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lines between midpoints
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Ogive
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graph that represents cumulative frequencies
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Relative Frequency graph
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proportions instead of raw data
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Pareto Chart
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represent frequency distribution for a categorical variable- vertical bars highest to lowest
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Pie Graph
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sections according to percentage of frequencies
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