Introduction to Statistics

1. Write hypotheses using symbols and words a. H 0 : µ ≤ 60 (population mean we were given) i. Scores after the program yield results with a mean less than or equal to the normal score of 60 b. H 1 : µ > 60 (population mean we were given) i. Scores after the program yield results with a mean greater than the normal score of 60 2. Set alpha level and accompanying z-score a. α = 0.05 , z = 1.65 3. Use M and n to find σ M and accompanying z-score of M a. σ M = σ √ n b. Graph and stuff c. Make decision 4. Formally write the result if needed a. Scientific: “The Mean of the treated animals was significantly lower than the mean of the untreated population” or some shit 5. Find area of graph in critical region (Power) a. DRAW ALL THE SHIT!!!!!!! i. Sketch the graph, define critical region, label original graph as H 0 and treatment graph as H 1 1. Use σ M as your unit for the x-axis ii. Use means and z scores and shit

PSYC | 60 | Introduction to Statistics | study guides | 1. Write hypotheses using symb

Stats Terms  TYPES OF STATISTICS o Descriptive Statistics : Set of methods to describe data that we have collected  Ex. 80% of the people we surveyed specifically had the last name Gonzalez o Inferential Statistics : Set of methods used to make a generalization, estimate, prediction or decision  Ex. Population survey saying that 80% of all people in Mexico have last name Gonzalez  PARAMETERS AND STATISTICS o Parameter : Describes a population (Greek letters)  Ex. Average University student GPA o Statistic : Describes a sample (Roman letters)  Ex. Average UCSD student GPA o Statistic estimates a parameter  SAMPLING ERROR o Sampling Error : Discrepancy between the sample statistic and the true population parameter it is estimating o To reduce: Use large sample and random selection o Statistical Truth : We can only “prove” something if we can measure the population. As a result of sampling error, we can only ever determine “beyond a reasonable doubt”  TYPES OF SUBJECTS o Between : a characteristic that varies between subjects (e.g. age, gender etc.) o Within : a characteristic of individuals that varies with time (same individual compared at different points in time)  TYPES OF RESEARCH o Experimental : Mandatory to manipulate the variables, finds relationship between control and variable groups (finds causality) o Non - Experimental (Correlational) : Don’t manipulate variables (doesn’t find causality, more than 1 variable changed and no control) o Quasi - Experimental : No actual manipulation, but groups defined by “natural” variations, either between subjects or over time  EXPERIMENTAL METHOD o Control : No treatment o Variable : Receives treatment o Confounding Variable : Uncontrolled, source of error in interpretation  TYPES OF VARIABES o Continuous Variable : One for which, within the limits the variable ranges, any value is possible (e.g. time to finish something) o Discrete Variable : Doesn’t span all numbers, HAS to be whole (or have some limitation) (e.g. how many cookies I can eat)  TYPES OF SCALES o Nominal : Something named (e.g. color of shirt) o Ordinal : Rank order (1 st place, 2 nd place, etc.) (sorted in single line, no ambiguity) o Interval : Order of data points and interval between them (e.g. temperature) (CAN BE NEGATIVE!) o Ratio : Interval scale with a true 0 point (e.g. Kelvin)  MEAN, MEDIAN, AND MODE o Mode : Use when scale is nominal or if you’re trying to find the “most typical case” o Median : Use when a distribution contains small number of extreme scores OR undetermined values (usually in the middle) OR is open-ended (no upper/lower limit) o Mean ( x ) : Otherwise, use mean usually  SKEWNESS o Positive vs. Negative depends on the tail o Right Skew : Mode < Median < Mean o Left Skew : Mean < Median < Mode  VARIANCE AND STANDARD DEVIATION o Sum of deviations ALWAYS equals 0 o Sum of Squares (SS) = ∑ ( x − μ ) 2 = ∑ x 2 − ( ∑ x ) 2 N , where x = datum, µ = mean, and N = # of scores o Variance for Population = SS N = σ 2 o Variance for Sample = SS n − 1 = σ 2  Degrees of Freedom (df) = n − 1

PSYC | 60 | Introduction to Statistics | study guides | Stats Terms  TYPES OF STATIST

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