Exam # 1 Study Guide Lectures: 1 - 6EXAM 1-study guideCH1-CH5*do the practice hw problemsMain terms:(Formula sheet given on exam but be familiar with what the formula looks like for each so you choose the correct one when solving a problem.)Lecture 1-2 (1/27-1/29)CH1&2: 2elements -> continuous/discrete2 elements:- Research methods- StatisticsStatistics refers to…- Statistical procedures- Answer obtained from those procedures- Population- Sample- Sample populationo Sample2 main types of statistics:- Descriptive stats- Inferential statsVariables = ?What does the strength of a relationship mean? The strength is determined by how much change one variable can cause in the other.Studying relationships- Correlational study (observation)o CORRELATION DOES NOT EQUAL CAUSATION- Experimental: manipulation by researcher (of independent variable)- Independent Variable: manipulated- Dependent Variable: measured4 types of measurement:1. Nominala. qualitative2. Ordinal a. quantitativePSYC243 1st Edition3. Intervala. quantitative4. Ratioa. Quantitative - Qualitative vs quantitative- Continuous vs discreteLecture 3 (2/3)CH3: Frequency distributions- Relative frequency- Cumulative frequency- Relative cumulative frequency- Percentile- Histogram vs bar graph vs polygonDistributions (shapes of curves, - Normal distribution: (human characteristics are normally dist.= high frequency concentrated around a ‘mean’ value with the rest expanding out to the right/left tail)- Skewed : (+) and (-)- Bimodal- Rectangular Lecture 4 (2/5)CH4: central tendencyCentral Tendency - Mode, median, meano *mean: sensitive to OUTLIERS! Extreme data pts. Will pull your mean up/down and misrepresent the datao Median isn’t as sensitive: resistant to outliersUse the “mean” unless…o Mode: nominal datao Median/mode: skewed distributiono Median: ordinal dataBar graphs: nominal, ordinal dataLine graphs: interval, ratio dataLecture 5 (2/10-2/12)CH5: measures of variabilityPSYC243 1st EditionStandard Deviation: “Distance” or how far a score ‘deviates from a predicted score/the middle of a normal distribution- Size of deviation: how far a score is from the “mean”o Higher score = more deviation/farther distance from the “mean”o If the score is equal to the mean, the deviation = 0o (+) deviation = score is higher than the mean. (on the positive end of the scale/distribution curve)o (-) deviation = score is lower than the mean. (on the negative end of the scale/distribution curve)- population variance- population standard deviation- sample variance- sample standard deviation“statistics” vs “parameters”- statistics refers to ‘sample’: ‘sample statistics’- parameters refers to ‘population’: ‘population parameters’ (defines the overall population)bias vs unbias- sample variance: biased estimator of population variance.o *it underestimates the true population parameters because it’s only a ‘sample’ of the overall population. - How do you account for the bias in the formula? Replace N with N-1. The smaller the number on the dominator, the larger the resulting total value will be -> making the sample value larger and more representative of the larger population #.PSYC243 1st