StuDocu.com Exam notes sheet Foundations of statistics (Swinburne University of Technology) StuDocu is not sponsored or endorsed by any college or university Downloaded by Krystle Sky (krystle.sky@googlemail.com)
** ALL FIGURES TO 2 DECIMAL PLACES EXCEPT FOR P VALUE ** IF p < . 050 = significant. IF p >.050 = not significant. If p =. 000, report as p <. 001 ** DO NOT REPORT NEGATIVE FOR T VALUE ** ** PROBABILITY = P VALUE ** frequency PROPORTION = total number TOTAL OF ALL VALUES NUMBER OF NUMBERS MEAN X = MEAN DIFFERENCE = X a STANDARD DEVIATION = Sa Z SCORE Standardised value: number of standard deviations above the mean. Standardised Value=i data value - mean of pop Z= x-H standard deviation ? Below the mean = Negative score, Above mean = Positive score T SCORE Where standard deviation is unknown SIGNIFICANCE & SAMPLING In normal distribution, values fall within 95% (2.5 standard deviations of mean) Values which fall within this 2.5% are REGRESSION Y = a + b x X | X = I variable | Y = D variable | a = vert. intercept (constant). Describes average start size. I.e. new born guinea pig weights 50grams. a = 50. b = SLOPE /REGRESSION COEFFICIENT. Describes average change per period - ie, Guinea pigs weigh 70 grams more with each month of age. b = 70 Age 12 mth guinea pig = 50 + 70 x 12 (1440 grams) REGRESSION COEFFICIENT = Coefficients table [ IV] = X% OF THE VARIATION IN X CAN BE EXPLAINED BY THE LINEAR RELATIONSHIP BETWEEN X AND X NUSIANCE VARIABLES AND CONFOUNDING FACTORS Nuisance variables affect the dependent variable. Must design experiment to minimise the effects and/or evenly distribute the effects. Nuisance variables act as confounding factors. CONTROLLING NUISANCE VARIABLES Independent Groups Design: Random allocation to separate groups to undertake tests under different circumstances. I.e. Group 1 Driving with BAC of .00 and Group 2 BAC of .05. Does not minimise nuisance variables but distributes. Repeated Measures: Same participants undergo tests under different conditions several times. Introduces practice effects which sway results. Matched Pairs: Match participants with those very similar, then separate into groups to undertake tests under different circumstances. Time consuming and difficult to identify NV to match. OBSERVATIONAL = Natural and uncontrolled/uninfluenced observation EXPERIMENTAL = Manipulating the IV to observe effect on DV HISTOGRAM DISTRIBUTION Positively Skewed Symmetrical distribution Bimodal distribution Negatively skewed RELATIONSHIP STRENGTH [Pearsons Correlation] .75 and more = STRONG .45 - . 74 = MODERATE .25 - . 44 = WEAK .24 and less = EXTREMELEY WEAK IGNORE neg/pos, work from numerical value only COEFFICIENT OF DETERMINATION = r2. How much is result of correlation. PEARSONS R = r . Strength of relationship - can be distorted by outliers, should always check scatterplot. Can be used if scatterplot shows no curve. PVALUE FOR PEARSONS Correlations table[Sig] ** AVOID CAUSAL RELATIONSHIPS ** STRATIFIED RANDOM SAMPLING: Where one group outweighs the other and need to reflect appropriate proportions of