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PSY 2400 - Week 1

by: Natalie

PSY 2400 - Week 1 Psy 2400

GPA 3.7

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Chapter 1: - 2 Branches of Statistical Methods - Basic Concepts - Kinds of Variables text in red will be on exam 1 Professor: Dr. Talley/Littlefield
Statistical Methods
Amelia Littlefield
Class Notes
Psychology, Statistics
25 ?




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This 7 page Class Notes was uploaded by Natalie on Sunday September 4, 2016. The Class Notes belongs to Psy 2400 at Texas Tech University taught by Amelia Littlefield in Fall 2016. Since its upload, it has received 90 views. For similar materials see Statistical Methods in Psychology (PSYC) at Texas Tech University.


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Date Created: 09/04/16
PSY 2400 – Statistical Methods 09/01/2016 ▯ Chapter Concepts  2 branches of statistical methods  basic concepts  kinds of variables ▯ Learning Outcomes  Key statistical terms  Key measurement terms  Key research terms  Know the place of statistics in science  Understand summation notation ▯ Asses the situation  Statistics requires basic math skills  Inadequate basic math skills puts you at a disadvantage in this  course  Appendix A math skills assessment helps you determine if you  need a skills review ▯ Statistics, science and meaningful observation  Statistics = statistical procedures  Statistics are used to o Organize and summarize information o Determine what conclusions are justified based on the date  Goals of statistical procedures o Accurate and meaningful interpretation o Provide standardized ways to address testable hypotheses ▯ Why learn statistics?  It’s required to graduate  Increase your understanding of media graphics and research  articles  So you can learn how to do your own research, be the master of  your own destiny  Can improve your critical reasoning and intuitive understanding of  how the world works ▯ Populations vs. Samples  Population o The set of ALL the individuals of interest in a particular study (who do you expect the conclusions apply to?) o Vary in size; often quite large o Entire set of things of interest  E.g. the entire piggy bank of coins  E.g. the entire population of individuals in the US  Sample o A subset of individuals selected from a larger population  (who are you using to answer your research question?) o Usually intended to represent the population in a research  study o The subset of the population about which you actually have  information  E.g. a handful of coins  E.g. 100 men and women who answered an online  questionnaire about health care usage  Population symbols are GREEK to you, literally: o Mean = μ = Mu (pronounced “Mew”) o Standard deviation = σ = Sigma o Variance = σ2 = Sigma­squared  Sample Symbols are more familiar o Mean = M =  X o Standard deviation = SD = s o Variance = SD2 = s2  ▯ Why use samples instead of populations?  More practical and cost­effective to obtain information from a  sample than a population  The goal of research is to make predictions about entire  populations  Social and behavioral research is conducted by evaluating a  sample of individuals who are believed to be “representative” of a  population of interest ▯ Speaking statistically: variables and date  Variable o Characteristic or condition that changes or varies among  different individuals in your sample  Date set  o A collection of measurements or observations  Data (plural noun)  o Measurements or observations of a variable  Datum (singular noun) o A single measurement or observations o Commonly called a score or raw score  Variable = characteristic or condition that can have different values o E.g. level of stress; time of day; number of freckles  Value = any possible number or category a score can have o E.g. 0­10  Score = particular person’s variable value o E.g. a study participant rates her current level of stress as a  5 on a scale of 0­10 Methods of Sampling  Random selection o Choosing a sample so that every individual in the population  has an equal chance of being selected  E.g. using a random number table  Haphazard (or “convenience”) selection o Selecting a sample of individuals to study based on  whomever is available or happens to be around  This method can result in a sample that is not  representative of a population ▯ Parameters and Statistics  Parameter o  Value, usually a number, that describes a feature of the  population o derived from measurements of the individuals in the  population  Statistic o A value, usually a number, that describes a feature of the  sample o Derived from measurements of the individuals in a given  sample ▯ Soooo – what is statistics?  A branch of mathematics that focusses on the organization,  analysis, and interpretation of a set of numbers  Wo main branches of statistics o Descriptive statistics  Summarize and describe date from a sample o Inferential statistics  Draw conclusions based on sample data that you  expect will apply/generalize to the population of  interest ▯ Descriptive & Inferential Statistics  Descriptive statistics o Summarize o Organize o Simplify o Ex:  Tables  Graphs  Averages  Percentages  Inferential statistics o Used to make generalizations about the population o Interpret observed date o Common terminology  “margin of error” “statistically significant” ▯ Sampling Error  Fact: a sample is NEVER going to be identical to the populations  Sampling error is the difference, or amount of error, between a  sample statistic and the corresponding population parameter  Example: “margin of Error” in Voting Polls o “this poll was taken from a sample of registered voters and  has a margin of error of plus­or­minus 4 percentage points” ▯ Data structures, research methods, and statistics  Variables are observed or measured o “statistics’ describe the measured variable o there are categorical and numerical variables  relationships between variables o two variables are observed and measured o two ways used to determine whether a relationship exists  between two variable ▯ Relationships between variables  Correlational method (first way) o Only one group of participants o Two variables are measured for each participant o Goal is to describe direction (positive, negative) and strength of the relationship o Patterns in the data reveal relations among variables o Non­experimental method ▯ ▯ Limitations of correlational method  Can demonstrate the existence of a relationship  But does not provide an explanation for the relationship – “cannot  answer WHY?!”  Most importantly, does not demonstrate a cause­and­effect  relationship between the two variables ▯ Relationships between variables  Methods comparing groups of scores (second way) o One variable defines the groups o Scores are measured on a second variable o Both experimental and non­experimental studies rely on this  structure ▯ Experimental Method essentials  Goal of experiments is to demonstrate a cause­and­effect  relationship  The level of one variable is manipulated by the experimenter and  determined by random assignment  Control rules out influence of other variables o Individual difference variables o Environmental variables   


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