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### 39 Cards in this Set

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 Frequency Distribution A record of the frequence of scores located in each response category of what's being measured Interval Scale Ordered equidistant categories having an infinite # of intermediate values and an arbitrary zero point Correlation Method Observing the naturally occuring relationship b/w two or more variables (as one variable changes, how does the other change?) ex: shoe size and height Construct Hypothetical concepts (abstract ideas) Experimental Method Cause and effect relationship; requires manipulation of at least one variable & measuring another variable Hypothesis Specific testable prediction about the relationship b/w 2 or more variables. Nominal Scale (Categorical) Category with different names. No quantitative distinctions; numbers may serve as labels Ordinal Scale (ordered) Category names (or #'s) are represented in an ordered sequence of magnitude; numbers have very limited quantitative properties ex: attractiveness, job performance Ratio Scale Interval scale with an absolute zero point (absence of construct) ex: Kelvin, time Cumulative Frequency Add the frequency at and below each score. Scientific Method 1. Describe the question/problem. 2. Design study->collect data. 3. Analyze data, draw conclusions. 4. Revise theories. Operational definition Defining a construct by the manner in which the variable is used and measured. ex: What does intelligence look like (IQ) Key elements in any distribution 1. Set of possible scores 2. The frequency of scores at each category Variable characteristic that changes or is different from one individual to the next (something that is measured) Grouping Guidelines 1. Have about 10 intervals 2. Interval widths must be equals 3. Use simple numbers for interval widths 4. The lower limit of the interval should be a multiple of the interval widths (ex: 2,4,5,10) 5. Highest &/or lowest interval should not have a zero frequency Experimental Group Receives the treatment level of the Ind. Var. Apparent Limit The actual limits of each interval (w/ gaps) ex: 6.5-6.9 Real (Exact) Limit Limits of the entire interval (closing the gaps) -always represented with one more place past the decimal that the apparent limit Confounding Variable Uncontrolled variable that can systematically vary with the ind. var. Midpoint In the exact middle of the interval Quasi-Experiment Nonmanipulated Ind. Var. Random Assignment For each participant, equal chance for assignment to each condition (Holds extraneous variables constant) Statistics A set of methods and rules for organizing summarizing and interpreting information. Control Group Does not receive the treatment level of the Ind. Var.;gets treatment or gets placebo treatment Independant Variable The variable that is manipulated (or controlled) ex: different groups; positive vs. negative words Dependent Variable The variable that is observed/measured. Inferential Statistic Procedures used to generalize the characteristic of a sample of a population (Infer to the population) Theory Integrated set of principles that explain all the facts and predicts observed events. Qualitative Difference Change in kind/quality ex: eye color, different drugs Continuous Variable Variable with an infinite # of possible intermediate values b/w any two values, qualitative differences. ex: time, distance, weight Quantitative Difference Change of amount ex: different amounts of drugs Discrete Variable A)Represents seperate categories for each level of the variable with no intermediate values B) Qualitative differences ex:gender, # of students Parameter Numerical value that describes a characteristic of a population. Population Set of individual of interest in a particular study. Random Sampling Process of obtaining a sample that requires every individual in the population has equal chance of selection (representatives of whole population) Statistic Numerical value that describes a characteristic of a sample Sample Set of individuals selected from a population who are intended to represent the population in research study. Sampling Error The numeric difference that usually exists b/w the sample statistic & population parameter ex) voting prediction, (aka: margin of error) Descriptive Statistics Procedures used to summarize, organize, and simplify data (describe)