Exam 1 Content Flashcards
Nominal Scales
classified into one of the categories and then counted for frequency
Ordinal Scales
gives quantitative order to variables (rank order scale)
Interval Scale
equal intervals of measurement
Ratio Scale
based on order, has equal distance between scale points, and uses zero to represent the absence of value
Null Hypthoesis
predicts no difference between groups (x=z)
Alternate Hypothesis (research hypothesis)
predicts a difference between groups
Independent Variable
manipulated by researcher
Dependent Variable
the outcome
Statistical Inference
process of generalizing from a sample to a population
Population
a group of things that all have at least 1 common characteristic
Sample
portion of population
Central Limit Theorem
states that the sum of random numbers become normally distributed as more numbers are added
Mesokurtic Curves
frequency tapers off symmetrically towards the tail
Platykurtic
thinner and longer tails than normal distribution (longer)
Leptokurtic
less tails than normal distribution (higher)
Skewness
measure of bilateral symmetry
Equation for Skewness
(Sum of Z^3)/N
Kurtosis
Measure of the relative heaviness of the tails
Equation for Kurtosis
(sum of Z^4/N)-3.0
Standard Error Factor for Skewness
SqrRoot(6/N)
Standard Error Factor for Kurtosis
SqrRoot(24/N)
Positively Skewed
tail to the right
Negatively Skewed
Tail to the left
Z-Score
raw score expressed in standard deviations
X
mean
SD
sample mean
Sigma or Mu
population mean
Z Score Equation
X-X/Sigma
Sampling Error
amount of error in the estimate of a population parameter that is based on a sample statistic
Standard Error of the Mean
indicates the amount of error that may occur when a random sample mean is used as a predictor of the mean of the population
Equation for Standard Error of the Mean
SD/SqrRoot(N)
Sampling Distribution of the Mean
frequency distribution of the sample means
Equation for Sample Distribution of the Mean
Mu= X +/- 1(SEm) where X=sample mean and Mu=pop mean
Level of Confidence
Percentage figure that establishes the probability that a statement is correct
Probability of Error
If x is the chance of being incorrect than p<.x
Confidence Interval
range of values associated with a level of confidence
Equation to find Confidence Interval
Mu = X +/- Z(SEm)
Type I Error
Rejected H but it is true (alpha)
Type II Error
Accepted H but it is false (B)