Exam 2 Psych 09/25/2012
Normal distribution can have any mean or STD
Standard Normal distribution has a mean of 0 and a STD of 1.
The process of standardization uses the zscore formula to turn the normal dist. into standard normal dist.
This allows us to compare by getting rid of different units.
In any normal distribution mean = median = mode
Histograms a common way to represent data, it shows yaxis percent/ proportion xaxis is intervals
Distribution a set of scores, set of data
Probability density function: continuous frequency distribution
Top bars are joined together in curved line
Proportion on yaxis
Skews: refers to long tail of distribution
Positive: tail to right
mode is smaller
median is bigger
Negative: tail to left
mode is larger
median is smaller
Normal Distribution: bell shaped curved, the lines curve down infinitivally towards the x axis, however it
never touches the x axis.
Inflection points there are 2 on a normal distribution, at 1 STD above and below the mean, symmetric, the
normal curve represents a perfectly normal distribution
Inflection point is where the curve changes direction concave down than concave up at 1STD.
Total area below the curve equals 1 or 100%; Allows for proportion (and probability) which allows us to
Normality assumption allows for performance of statistical tests. Sampling distribution of the mean is a
normal distribution ZScores: Any normal distribution can be transformed istandard normal distribution – Standardization
x − μ
⇒ x = zσ + μ
x whatever given score
u (mu) – mean of population (only dealing with pop)
sigma STD of population
z score value is positive – means it is above mean
if z score is neg it is below the mean
“68 – 95 – 99.7” rule: proportion of scores that falls between +/1 SD, +/2 SD, & +/3 SD
Proportions under a normal curve: percentage = proportion = probability
Analytic view: definition of probability in terms of analysis of possible outcomes
“probabilities from models”
doesn’t have to be executed: don’t have to perform this activity
you know this ahead of time; theo