Chapter 3 - Some Key Ingredients For Inferential Statistics

Front 1

Z Score

Back 1

Number of standard deviations that a score is above (or below, if it is negative) the mean of its distribution; it is thus an ordinary score transformed so that it better describes the score’s location in a distribution.

Front 2

Raw Score

Back 2

Ordinary score (or any number in a distribution before it has been made into a Z score or otherwise transformed)

Front 3

Steps to Change a Raw Score to a Z Score

Back 3

1. Figure the deviation score: subtract the mean from the raw score

2. Figure the Z score: divide the deviation score by the standard deviation.

Front 4

Steps to Change a Z Score to a Raw Score

Back 4

1. Figure the deviation score; multiply the Z score by the standard deviation.

2. Figure the raw score; add the mean to the deviation score.

Front 5

Normal Distribution

Back 5

Frequency distribution that follows a normal curve.

Front 6

Normal Curve

Back 6

Specific, mathematically defined, bell-shaped frequency distribution that is symmetrical and unimodal; distributions observed in nature and in research commonly approximates it.

Front 7

Steps for Figuring the Percentage of Scores Above or Below a Particular Raw Score or Z Score Using the Normal Curve Table

Back 7

1. If you are beginning with a raw score, first change it to a Z score.

2. Draw a picture of the normal curve, decide where the Z score falls on it, and shade in the area for which you are finding the percentage.

3. Make a rough estimate of the shaded area’s percentage based on the 50% - 34% - 14% percentages.

4. Find the exact percentage using the normal curve table, adding 50% if necessary.

5. Check that your exact percentage is within the range of your rough estimate from Step 3.

Front 8

Population

Back 8

Entire group of people to which a researcher intends the results of a study to apply; larger group to which inferences are made on the basis of the particular set of people (sample) studied.

Front 9

Sample

Back 9

Scores of the particular group of people studied; usually considered to be representative of the scores in some larger population.

Front 10

Probability

Back 10

Expected relative frequency of an outcome; proportion of successful outcomes to all outcomes.

Front 11

Outcome

Back 11

Term used in discussing probability for the result of an experiment (or almost any event, such as a coin coming up heads or it raining tomorrow)

Front 12

Expected Relative Frequency

Back 12

Number of successful outcomes divided by the number of total outcomes you would expect to get if you repeated an experiment a large number of times.

Front 13

Long-Run Relative-Frequency Interpretation of Probability

Back 13

Understanding of probability as the proportion of a particular outcome that you would get if the experiment were repeated many times.

Front 14

Subjective Interpretation of Probability

Back 14

Way of understanding probability as the degree of one’s certainty that a particular outcome will occur.

Front 15

Steps for Finding Probabilities

Back 15

1. Determine the number of possible successful outcomes.

2. Determine the number of all possible outcomes.

3. Divide the number of possible successful outcomes (Step 1), by the number of all possible outcomes (Step 2).

Front 16

Random Selection

Back 16

Method for selecting a sample that uses truly random procedures (usually meaning that each person in the population has an equal chance of being selected); one procedure is for the researcher to begin with a complete list of all the people in the population and select a group of them to study using a table of random numbers.