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social science statistics exam 1
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Terms in this set (43)
descriptive statistics
numbers that are used to summarize and describe data
inferential statistics
statistical methods that make it possible to draw tentative conclusions about the population based on observations of a sample
dependent variable
the variable that we do not directly introduce or manipulate
independent variable
the variable that is associated with different values of the dependent variable
confounding variable
variables that are in a specific way that cannot be separated
one-tailed hypothesis
researcher predicts that a statistically significant relationship between variables will be found and it predicts the direction of the relationship
two-tailed hypothesis
predicts a significant relationship or difference, but not the specific nature.
null hypothesis
2 sets of data are not statistically different from each other
univariate analysis
statistical analysis of the distribution of values of a single variable
bi-variate analysis
a statistical analysis of the relationship between two variables
multivariate analysis
a statistical analysis of the simultaneous relationship among three or more variables
constant
a characteristic that has the same value for all individuals
operationalization
Defining variables in practical terms.
reliability
Consistency of a measurement instrument
validity
the degree to which a measurement instrument accurately measures what it is supposed to measure
mode
The value that occurs most frequently in a given data set.
median
the middle score in a distribution; half the scores are above it and half are below it
mean
the Average
weighted mean
the average of a group scores that are weighted to reflect their different levels of importance
trimmed mean
a measure of central tendency calculated by first trimming a small percentage of values off the upper and lower limits of an array of case values and then averaging the remaining values
range
the difference between the highest and lowest scores in a data set
interquartile range
The difference between the upper and lower quartiles.
Outlier
an extreme value of a data set that is either larger or smaller than most other values in the variables distribution
normal curve
a symmetrical, bell-shaped curve that describes the distribution of many types of data
standard deviation
a common measure of variability, which requires at least interval level data and reflects the value of every observation in the distribution
percentile rank
a transformed score that tells us the percentage of scores falling at or below a given score
raw score
a numerical value assigned to an observation that is expressed in the original units of measurement
z score
a measure of how many standard deviations you are away from the norm (average or mean)
mesokurtic distribution
a frequency distribution that is neither excessively peaked nor excessively flat
leptokurtic distribution
a relatively peaked frequency distribution; a frequency distribution that is more concentrated around the mean than the corresponding normal distribution
platykurtic distribution
a frequency distribution that has a relatively flat shape
type 1 error
error that occurs when the null hypothesis is rejected when a true relationship between variables does not exist
type 2 error
error that occurs when the null hypothesis is not rejected when a true relationship between variables exists
sampling error
the difference between the results of random samples taken at the same time
sampling distribution
a theoretical distribution that can be specified for any statistic that can be computed for samples from a population
confidence interval
a range of values within which we are willing to assert with a specified level of confidence
rejection region
a specific region of a normal curve that when it contains a measurement from a sample
standard error of the mean
The standard deviation of the sampling distribution of the sample mean
statistic
a numerical measurement describing some characteristic of a sample
parameter
a characteristic of a population determined from observations on every member of the population
measures of central tendency
mean, median, mode
variability
dispersion of a distribution, the extent to which values differ among themselves
effect size
the percent of a variance in the dependent variable that can be explained by the independent variable
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