Reading...
Play button
Play button
Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
46 Cards in this Set
- Front
- Back
|
Case
|
A unit of study (person, cars, animals, etc.)
|
|
|
Subject
|
A unit of study that is human
|
|
|
Central tendency
|
A summary statistic; location within a distribution. A score that is representative of the entire set of scores. Can be described by mode, median, and mean.
|
|
|
Outliers
|
Scores that are way out of line with the rest of the data. May be legitimate – or result of clerical error. They can markedly affect the mean. If there are several outliers, median may be useful.
|
|
|
Rank Order Data
|
Scores are placed in numerical order and then assigned (usually descending) rank. The difference between the adjacent ranks may not be equal. Two sets of ranks can be analyzed by the Spearman Rho.
|
|
|
Inferential statistics
|
Using collected data to draw conclusions about the larger group (popoluation) from which the sample was drawn.
|
|
|
Skewed distribution
|
A measure of asymmetry in distribution. Negative skew, a lot of high numbers, the tail is to left. Positive skew, a lot of low numbers, tail is to right. Leptokurtic has many middle scores and is tall. Platykurtic has few middle scores and is flat.
|
|
|
Quantitative
|
Data associated with a scale number. Numerical data that can be analyzed.
|
|
|
Range
|
A measurement of dispersion which is equal to the difference between the highest and lowest scores in a set of data
|
|
|
Median
|
Cuts distribution in half. It will be the centermost score- or ½ the sum of the two centermost scores.
|
|
|
Mode
|
The most frequent score. The value that occurs most often. May use a frequency table to determine if there are many scores to work with.
|
|
|
Variable
|
When the value of a trait is being measured from case to case-that trait is the variable- such as the running speed of sophomores
|
|
|
Variance
|
The average area distance from the mean
|
|
|
Mean
|
The average of all the scores (add all scores and divide by n). Most statistical analyses builds on the mean.
|
|
|
The value of variance
|
The computation of variance, the average area from the mean, is required to compute the standard deviation, or the linear measure from the mean. Also useful when computing the common variance (or overlap) of two sets of scores.
|
|
|
Bimodal distribution
|
A distribution with two peaks- indicating there may be distinct subgroups
|
|
|
The Null
|
The null hypothesis (H0) states that there is no expected effect on the DV by the IV. Key phrase is “no difference”. It is the usually used as a straw a man the researcher hopes to knock down.
|
|
|
Know how to read ANOVA
|
ANOVA stands for analysis of variance- describes the between groups variances, use F test.-The df between groups is the numerator df-The df within groups is the denominator df-df between groups is always listed first-Type 1 errors are listed at 1% (higher number) and 5% (lower number)-The values listed are the minimum numbers that allow us to reject the null hypothesisF(2,27)=14.1, p<.01
|
|
|
Qualitative observation
|
Using natural language to place in categories- named- numbers are for organization- researcher uses words to describe
|
|
|
Three types of statistics correlation
|
Used to see if two different scores, on two variables, are related. These scores are from a single group of subjects. Used to test reliability. Also used to predict- by establishing relationship between scores- one of the variables can be used to predict the other. Correlation is also used define relationships strength and direction. Relationships can also be positive, negative, or zero.
|
|
|
Descriptive
|
Statistics that say something about the actual sample- the members of the study- the group is described. The information gathered may then be applied to the larger sample and inferences made, based on the descriptive data of the sample.
|
|
|
Two tailed vs. one tailed test
|
A one-tailed test is directional and is looking for a specific direction- higher than, lower than. In a one-tailed test, there is one region of rejection, and one region of retention.A two-tailed test is non-directional and is looking for difference only, not which direction the difference is in. Both tails will reject the null hypothesis- with the center of the distribution retaining it.
|
|
|
Nominal Scale
|
Ranks in to categories, designations without numerical meaning- lowest form of measurement
|
|
|
Case
|
A unit of study (person, cars, animals, etc.)
|
|
|
Subject
|
A unit of study that is human
|
|
|
Central tendency
|
A summary statistic; location within a distribution. A score that is representative of the entire set of scores. Can be described by mode, median, and mean.
|
|
|
Outliers
|
Scores that are way out of line with the rest of the data. May be legitimate – or result of clerical error. They can markedly affect the mean. If there are several outliers, median may be useful.
|
|
|
Rank Order Data
|
Scores are placed in numerical order and then assigned (usually descending) rank. The difference between the adjacent ranks may not be equal. Two sets of ranks can be analyzed by the Spearman Rho.
|
|
|
Inferential statistics
|
Using collected data to draw conclusions about the larger group (popoluation) from which the sample was drawn.
|
|
|
Skewed distribution
|
A measure of asymmetry in distribution. Negative skew, a lot of high numbers, the tail is to left. Positive skew, a lot of low numbers, tail is to right. Leptokurtic has many middle scores and is tall. Platykurtic has few middle scores and is flat.
|
|
|
Quantitative
|
Data associated with a scale number. Numerical data that can be analyzed.
|
|
|
Range
|
A measurement of dispersion which is equal to the difference between the highest and lowest scores in a set of data
|
|
|
Median
|
Cuts distribution in half. It will be the centermost score- or ½ the sum of the two centermost scores.
|
|
|
Mode
|
The most frequent score. The value that occurs most often. May use a frequency table to determine if there are many scores to work with.
|
|
|
Variable
|
When the value of a trait is being measured from case to case-that trait is the variable- such as the running speed of sophomores
|
|
|
Variance
|
The average area distance from the mean
|
|
|
Mean
|
The average of all the scores (add all scores and divide by n). Most statistical analyses builds on the mean.
|
|
|
The value of variance
|
The computation of variance, the average area from the mean, is required to compute the standard deviation, or the linear measure from the mean. Also useful when computing the common variance (or overlap) of two sets of scores.
|
|
|
Bimodal distribution
|
A distribution with two peaks- indicating there may be distinct subgroups
|
|
|
The Null
|
The null hypothesis (H0) states that there is no expected effect on the DV by the IV. Key phrase is “no difference”. It is the usually used as a straw a man the researcher hopes to knock down.
|
|
|
Know how to read ANOV
|
AANOVA stands for analysis of variance- describes the between groups variances, use F test.-The df between groups is the numerator df-The df within groups is the denominator df-df between groups is always listed first-Type 1 errors are listed at 1% (higher number) and 5% (lower number)-The values listed are the minimum numbers that allow us to reject the null hypothesisF(2,27)=14.1, p<.01
|
|
|
Qualitative observation
|
Using natural language to place in categories- named- numbers are for organization- researcher uses words to describe
|
|
|
Three types of statistics correlation
|
Used to see if two different scores, on two variables, are related. These scores are from a single group of subjects. Used to test reliability. Also used to predict- by establishing relationship between scores- one of the variables can be used to predict the other. Correlation is also used define relationships strength and direction. Relationships can also be positive, negative, or zero.
|
|
|
Descriptive
|
Statistics that say something about the actual sample- the members of the study- the group is described. The information gathered may then be applied to the larger sample and inferences made, based on the descriptive data of the sample.
|
|
|
Two tailed vs. one tailed test
|
A one-tailed test is directional and is looking for a specific direction- higher than, lower than. In a one-tailed test, there is one region of rejection, and one region of retention.A two-tailed test is non-directional and is looking for difference only, not which direction the difference is in. Both tails will reject the null hypothesis- with the center of the distribution retaining it.
|
|
|
Nominal Scale
|
Ranks in to categories, designations without numerical meaning- lowest form of measurement
|
