PSY 103 Mod 1 Statistics Notes PDF
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These notes cover introductory statistics, focusing on descriptive and inferential statistics. It also introduces the concepts of variables and measurement scales. The document covers different types of variables and their measurement scales, parametric vs. non-parametric statistics, and research design.
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psy 103 mod 1 Statistics Statistics - range of techniques for analyzing interpreting,displaying,...
psy 103 mod 1 Statistics Statistics - range of techniques for analyzing interpreting,displaying, and making decisions based on data. Describing set of data the Inferential Involved small group > general Descriptive researcher Collected statement for the larger population Psychological statistics Analyze a collection of numerical facts about psychology make conclusions Present. Organize Summarize make use STATISTICAL METHODS that are commonly applied to the analysis of psychological data Data- usually numerical data with no meaningful description Types of variables Variables - character that varies across (nababago), Dependent ( criterion) Independent (causal) Constants - Remains same Outcome - Cause Discrete- No intermediate values (no of child in a family) Continuous - can take any values within given range (height) Categorical - are characterized by categories or groups (gender) Discrete vs Continuous vs Categorical. Scales/Levels of Measurement Nominal-possible values are unordered Ordinal- there is magnitude (values are in order) Interval-no absolute zero Temperature Ratio- has absolute zero. Parametric vs Nonparametric Statistics Parametric statistics - stats based cn distributions and their parameters Assumptions of Parametric Statistics Normal Distribution Random Sampling Interval/Ratio Level of Measurement Homogeneity of Variance Nonparametric statistics- if scale does not meet normal * failed to meet even one criteria of parametric Types research design Statistics and Research Quantitative Qualitative Mixed methods Population - collection of people who could be measured Sample- a representative subset of the population Numerical Descriptive analysis A probability sample is more likely to represent the population (external validity) than a nonprobability sample. Experimental Quasi experimental non-experimental Research design Experimental- causation/ random sampling and assignment I manipulation at IV Sample and sampling methods Quasi-experimental - "experiment-like" / not random sampling / manipulation of IV Probability Non probability Non-experimental- descriptive 1 correlation/ Purposive regression/comparative Random Snowball Stratified Convenience Systematic Incidental Cluster Psy 103 mod 2 Frequency tables -Used to organize, describe, and interpret data in a more meaningful manner Array-commonly arranged from highest to lowest Simple frequency table - use for large number of observations 2 column table(possible scores| frequency Cumulative frequency (Cf)- from F of the lowest score ) add up Relative frequency-tells us what proportion of the group attained each score Cumulative relative frequency (crf) Cumulative percent frequency (cpf) Graphing your results Bar graph- used for discrete and categorical type of data Histogram - used for continous data line graph- timeline Pie chart (no more than five) use of percentage Grouped frequency distribution - grouping the scores into equal-sized intervals (class intervals) - usually for measurements on an interval/ratio scale Apparent limit that values seen Ina class First lower apparent 60-64 Second upper apparent Real limits (class boundaries) - the lower real limit is.5 less than the lower apparent limit (59.5) - the upper real limit is.5 greater than the upper apparent limit (64.5) * Real limit remove the gaps (for continuous data Psy I03 mod 3 MCT Measures of central tendency Summarize a sample by single typical value Mean Median Mode Mean- most useful Add and divide W number of data Median - middle of distribution Array and find middle value Unimodal Multimodal mode- the most occurring Array and find mc Bimodal Unimodal -Normal distribution Bimodal-two meaningful modes multimodal-Distribution with move than 2 peaks Positive skewness-Floor effect (mean >median>mode ) Negatively skewed-floor effect (mean