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Oct 11 Notes.docx

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John Kervin

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Kranzler Chapter 6-The Normal Curve • A curve with normal distribution Features of Normal Curve (all differ in terms of their means and standard deviation) • Symmetric around the mean (so the left side mirror the right side of the mean) • Unimodal (because they are symmetric so the most frequently observed –mode-is the same as the mean) • Since unimodal and symmetric, the mean, mode and median are equal • Asymptotic to the horizontal axis of distribution. The curved descends rapidly from the center, as you move along the horizontal axis. But it never touches the horizontal axis and is continuous as it is used to describe an infinity of observations • All normal curves have the same proportion of scores under the curve relative to particular location on the horizontal axis when the scores are expressed in a similar basis (i.e., in standard score) The Normal Curve as a Model ( • Good description of the distribution of many variable in social and behavioural sciences (IQ test) • Sampling distribution: frequency distribution of the means of those sample, the distribution of those statics would approximate the normal curve • Ex. University students (16) and prof wants to know average age (u) and n= sample size (3/16) o Prof randomly selects 3 students and finds out their ages and calculate sample mean (x) o Use sample mean to estimate u (actual average age) and give measure of uncertainty o Sample mean is going to vary from sample to sample o If we sample many times, the graph would reflect the normal curve and closely resemble the true sampling distribution Proportions of Scores Under Normal Curve • If you know the mean of group, and that the distribution is normal, then the mode is median • Standard deviation; 68.26 cases would have between range of (mean-standard deviationSX) to (mean + standard deviation) • So 13.59 % cases are going to between the range of SD-2 and the mean and 13.59 % are going to be between the cases of SD+2 –mean • Pg 59 Chapter 7-Percentile and Standard Scores • Raw score don’t communicate much information (98/200) Percentiles • Percentile rank of score in a distribution is the percentage of the whole distribution falling below that score, plus half the percentage of distribution falling exactly on that score Standard Scores • Convert raw scores into standard scores (more meaningful) • Z score, related the score in relation to the mean in standard deviation unit • Z = (X-mean)/SD X Z scores Properties • Mean of
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