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34 Cards in this Set
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What is the primary purpose of inferential statistics 
To make a judgment about a population, or the total collection of all elements about which a researcher seeks information


Sample Statistics

Measures computed from sample data


Population parameters

measured characteristics of a specific population


Frequency Distribution

A set of data organized by summarizing the number of itmes a particular value of a variable occurs


Percentage Distribution

A frequency distribution organized onto a table that summarizes percetnage vlaues associated with particular values of a variable


Probability

The long run relative frequency with which an event will occur


Top Box Scores

Proportion of respondents who chose the most positive choice in a multiple choice quesiton


Measures of Central tendency

Mean Median and Mode


Mean

The arithmetic average


Median

The midpoint; the value below which half the values in a distirbution fall


Mode

The value that occurs most often


The Range

The distance between the smallest and the largest values of a frequency distribution


Deviation Scores

Indicate how far any observation is from the mean dii=Xi  X


Variance

A measure of variability or dispersion. It's square root is the standard deviation


Standard Deviation

A Quanititative index of a distribution spread, or variability; the square root of the variance for a distribution.
The average of the amount of variance for a distribution. USed to calculate the likelihood of an event occurring. 

Normal Distribution

A symmetrical bell shaped distribution (normal curve) that describes the expected probabiltiy distribution of many chance occurences. 99% of it's values are within +/ 3 standard deviations from its mean


Standardized Normal Distribution

A purely theorietical probability distribution that reflects a specific normal curve for the standard value, z.


What are the characteristics of a Standardized Normal Distribution

It is symmetrical about its mean
The mean identifies the normal curve's highest point and the vertical line about which this normal curve is symmetrical The normal curve has an infinite number of cases and the area under the curve has a probabilty desnity equal to 1.0 The standardized normal distirbution has a mean of 0 and a standard deviation of 1 

Standardized Values

Used to compare an individual value to the population man in units of the standard deviation


Population Distribution

A frequency distribution of a population


Sampling Distribution

A theoretical probability distribution of sample means for all possible samples of a certain size drawn from a particular population


Standard Error of the Mean

The standard deviation of the sampling distribution


Central Limit Theorem

The theory that as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution


Point Estimate

An estimate of the population mean in the form of a single value, usually the sample mean


Confidence Interval Estimate

A specified range of numbers iwthin which a population mean is expected to lie
An estimate of the population mean based on the knowledge that it will be equal to the sample mean plus or minus a sampling error 

Confidence Level

A percentage or decimal value that tells how confident a researcher can be about being correct. It states the long run percetnage of confidence intervals that will incldue the true population mean. The crux of the problem for a researcher is determine how much random sampling error to tolerate. Traditionally, reaserchers have used the 95% confidence level (a 5% tolerance for error)


S

Standard Deviation


E

Magnitude of Error


Zcl.

Confidence Level


Approximate value of the population mean

X +/ Zcl.Sx


diminishing returns

random sampling error is inversely proportional to the square root of n.


Variance (or Heterogeneity)

A heterogeneous population has more variance (a larger standard deviation) which will require a larger sample. A homogenous population has less variance which permits a smaller sample


Magnitude of Error (Confidence Interval)

How precise the estimate must be


Confidence Level

How much error will be tolerated
