Exam 2 Psychology Statistics

the normal curve

bell-shaped and has “tails” that extend infinitely in both directions

-1 and +1 =

68%

-1 and 0 =

34%

-2 and +2 =

95%

-3 and +3 =

99%

area below a positive z score =

B column +0.50 × 100

area above a positive z score =

C column

area below a negative z score =

C column

area above a negative z score =

z score + B column + 0.50 × 100

calculate between scores percentages

• calculate the Z score for both scores

• find the Z scores in the normal curve table

• use the B and C columns of the table to determine the area

describe the concept of standardization

• the process of putting different variables on the same scale

• descriptive- describing the people we are sampling

• inferential- first branch + estimation

• gives us a consisent way of looking at data

descriptive statistics

describing the people we are sampling

inferential statistics

first branch = estimate

alpha

the higher your alpha, the lower your confidence interval

expressed as a proportion (generally 0.05 relative to C.I. 95%)

central limit theorem

• the larger your sample the closer to normal distribution

• a theorem that specifies the mean, standard deviation, and the shape of the sampling distribution, given that the sample is large

concept of bias

a frequently used alternative way of expressing alpha, the probability that an interval estimate will not contain the population value. Confidence levels of 90%, 95%, 99%, and 99.9% correspond to alphas of 0.10, 0.05, 0.01, and 0.0001, respectively

EPSeM

the equal probability of Selection Method for selecting samples. Every element or case in the population must have an equal probability of selection for the sample

nonprobability sample

any sample that does not meet the EPSeM criterion

probability sample

everyone has a chance (using EPSeM)

sample

empirical (observable) and known, it is the group from which we collect our data (known information)

population

Distribution is a known group of all possible cases that meet some definition. Estimating the population is the goal of inferential statistics

sampling distribution

the distribution of statistics for all possible sample outcomes of a certain size. They are theoretical, not empirical

calculate confidence intervals

C.I. = Mean +/ -Z(SD/sqrt n-1)

describe the characteristics of a representative sample

want the sample to represent the essential characteristics of the population

effciency

the extent to which the sample outcomes are clustered around the mean of the sampling distribution

parameter

a characteristic of a population

the process of hypothesis testing for a one-sample case

statistic test that estimates the probability of sample outcomes if assumptions about the population (the null hypothesis are true)

type one and type two errors

type 1- rejecting the null hypothesis which is true (of no differences that are more common)

Type 2 fails to reject the null hypothesis when you should have (when needing to reject it)

• the higher the alpha the higher the likelihood to commit type 1 error