Chap 9 Exploring Statistics PDF

Chap 9 Exploring Statistics and Statistical Package for Social Science Exploring Statistics and Statistical Package for Social Science I. Statistics and Other Related Concepts Levels of Measurement - help us determine what statistical technique is appropriate to use....

Chap 9 Exploring Statistics and Statistical Package for Social Science Exploring Statistics and Statistical Package for Social Science I. Statistics and Other Related Concepts Levels of Measurement - help us determine what statistical technique is appropriate to use. Nominal (Meaning Ordinal Interval Ratio Name) Categorize/ Classify/Name Data Rank Data in there is no order order/Hierarchy between categories/ classification Has/Possess the Nothing can be Property of said about the Equal Intervals intervals between rankings Has/Possess the There is no true Property of zero Absolute Zero point/ absolute zero meaning “The values of the data can go below 0” or “The 0 has meaning/value” Examples City of birth Top 5 Olympic Test scores (e.g., Height Gender Medallists IQ or Age Ethnicity Language exams) Weight Car brands Ability (e.g., Personality Temperature Marital status beginner, Inventories in Kelvin intermediate, Temperature in fluent) Fahrenheit or Likert-type Celsius questions (e.g., very dissatisfied to very satisfied) Republican, Small–8oz, 1 dollar to 2 dollars Day 0, Day 1, Democrat, Medium–12oz, is the Day 2, Day 3 Green, Libertarian Large–32oz same interval as 88 dollars to 89 dollars Categories Names Colors Labels Names Favorite foods ‘yes’ Labels or Favorite foods ‘yes’ ‘no’ responses or ‘no’ responses A list of the top five national parks  Socioeconomic Status Trait/Personality Developmental Self-esteem Types Stages Life satisfaction Types of Disorders Levels of Loneliness Attachment style Consciousness Shyness Emotions Maslow’s Optimism Gardner’s Theory Hierarchy of Cognitive of Needs performance Multiple Intelligence Salary Grade Aggressiveness Defense Latin Honors Motivation Mechanisms Concentration / attention Self-regulation, self-control Group cohesion Gender Pain scale (0-10) Temperature Age Ethnicity Age groups (18- IQ Height Marital status 25, 26- SAT score Weight Zip code 35, etc.) Depression score BP Religious Affiliation Grade (A, B, C, D, Time of day HR Medical Diagnosis & F) Dates (Years) Years of Names of Satisfaction scale Experience Medications (poor, Time to complete acceptable, good) a task Performance scale (Below average, average, above average) Measures of Central Tendency/Central Location - attempts to describe a set of data by identifying the central position within that set of data - tells where most of the score/points lie Test Purpose Mean - Average - For INTERVAL/RATIO & normally distributed Data - Most commonly used Median - Middle Score - For ORDINAL, INTERVAL/RATIO Data - Used when few scores lies either at high end or low end of the distribution (Skewed Distribution) Mode - Most Frequent/Repeated Score - For Nominal Data - Useful in analysis of qualitative or verbal nature - Least commonly used Measures of Variability/Dispersion/Scattering/Spreading - describes how far apart data points lie from each other and from the center of a distribution - summarizes how far apart the scores are - Small/Low variability = values/scores are more consistent - Large/High variability =values/scores are less consistent Range - Highest minus lower score  - For ORDINAL Data Semi Interquartile - third quartile (Q3) minus the first quartile (Q1) divided by 2 Range - Or interquartile range (Q3-Q1) divided by 2 - For ORDINAL Data Standard Deviation - Dispersion of a dataset in relation to the mean - Calculation: square root of variance - Tells how far each score lies from the mean - Larger SD = the more dispersed are the scores - For INTERVAL/RATIO Data Variance - reflects the degree of spread in the data set - Calculation: square of the standard deviation - The more spread the data, the larger the variance is in relation to the mean - For ORDINAL, INTERVAL/RATIO Data Parametric Tests Nonparametric Tests - Used when data Has normal distribution - Do not require normal distribution - Used when Level of Measurement: - Used when Level of Measurement: Nominal Interval or Ratio data and Ordinal - Used when conditions are not as stringent or controlled and when sample size is small (n