Research Methods 2

Correlation, chi-square and anova are - statistics. The mean, standard deviation, and skewness are - statistics.

bivariate, univariate

Type - errors are often produced by having insufficient -.

ii, power

A - is/are identified (in theory) by comparing the significant pattern found in the sample data with the pattern in the population, - is/are identified by comparing the significant pattern found in the sample data with the pattern that was expected based upon theory.

type iii error, results contrary to the research hypothesis

- statistics involve summaries of a single variable, - statistics summarize the relationship between two variables.

univariate, bivariate

- are measures/behaviors for which the set of participants have at least 2 different values, while - are measures/behaviors for which all participants have the same value.

variables, constants

The mean describes the - of the distribution, the standard deviation its - and and the skewness its-.

Center, variability, shape

When making between groups comparisons, - is used to ask if the participants in the different IV conditions have different response likelihoods, - is to ask if the participants in the different IV conditions have different response averages.

Chi-square, between groups anova

When you have repeated measures data, - tests hypotheses about prediction and - tests hypotheses about differences.

Correlation, WG ANOVA

When you mistakenly conclude the variables aren't related in the target population the type of statistical error is called a type - error or a -, when you correctly conclude the variables are related in the target population but get the direction or pattern of that relationship wrong the type of statistical error is called a type - error or a -, a type - error or a - is a statistical decision error made when you mistakenly decide the variables are related in the target population.

II, miss, iii, misspecification, i, false alarm

The - is the most common value, the - is the average value and the - is the middle most value.

Mode, mean, median

- variables are those for which different values indicate different kinds and - variables are those for which different values indicate different amounts.

Qualitative, quantitative

The - estimates the variability of scores around the population mean, the - estimates the variability of repeated estimates of population mean around the population mean.

Standard deviation, standard error of the mean

Using a larger sample size increases the chances of finding a - effect but doesn't increase the chances of finding a - effect.

Significant, large

The - of r tells the strength of the linear relationship, while the - of r tells the direction of the linear relationship.

Size, sign

- chi-square data patterns have row differences in the two columns, - chi-square data patterns often have a difference between the rows of only one column.

Symmetrical, asymmetrical

A - occurs when the significant pattern found in the sample data is different from the pattern in the population, - occur(s) when the significant pattern of results is different from the pattern we expected.

Type iii error, results contrary to the research hypothesis

When making between groups comparisons, - is used when the DV is qualitative and - is used when the DV is quantitative.

chi-square, between groups anova

If the H0: is true in the population a p>.05, this will lead you to make a -, if p is less than .05, you will make a - error of -.

correct retention, i, false alarm

When making tests of bivariate association, and - is used when the variables are quantitative - is used when the variables are qualitative.

correlation, chi-square

type - errors may be the result of poor sampling, poor measurement, sampling variability, and/or having a too-small sample, type - and type - errors don't involve having a too-small sample.

ii, i, iii

If the H0: is false in the population a p greater than .05, this will lead you to make a type - error (which is also called a -), and a p less than .05 will lead you to make a - of H0:.

ii, miss, correct rejection

Performing a correlation presumes there's a - bivariate relationship between the two variables, a correlation shouldn't be used if the variables have a - bivariate relationship.

linear, nonlinear

The - can be used with both quantitative and qualitative variables, while the - and the - can only be used with quantitative variables.

mode, mean, median

The - is the most common score of the distribution, the - is the balancing point of the distribution, and the - has 50% of the scores above and below it.

mode, mean, median

A scatterplot can be used to decide if two quantitative variables have a - bivariate relationship that can't be represented by a correlation or if the two quantitative variables have a - bivariate relationship.

nonlinear, linear

A/an - power analysis is performed after a study is conducted, a/an - power analysis is performed before the study is conducted.

post hoc, a priori

A/an - power analysis is performed when you retain the H0: to help estimate the probability of a Type ii error, a/an - power analysis is performed to determine the sample size that should be used for the study.

post hod, a priori

Having sufficient - decreases decreases the probability of making a type - error.

power, ii

- is used to measure a linear relationship, while - is used to compare different means

r, anova

- occur when we don't find the data pattern we "hoped for," a - occurs when we don't find the data pattern we "should have."

results contrary to the research hypothesis, type iii error

A - is used to display relationships between two quantitative variables a - used to display relationships between two qualitative variables.

scatterplot, contingency table

A - should be examined before a correlation is calculated, a - should be examined to describe the pattern revealed by a significant chi-square.

scatterplot, contingency table

The - of r is the "effect direction" and the - of r is the "effect size."

sign, size

The - of r isn't related to whether or not the correlation is significant, while the - is.

sign, size

A - effect is identified using the p-value, a - effect is identified using the r-value.

significant, large

The - measures the extent of a symmetry of the distribution, the - measures the spread of scores around the mean.

skewness, standard deviation

The - together with sample size is used to calculate the -, which estimates accuracy with which sample means represent the population mean.

standard deviation, standard error of the mean

Accuracy with which sample means represent the population mean is estimated by the -, which is calculated from the - and the sample size.

standard error of the mean, standard deviation

- chi-square data patterns are usually stronger effects than - chi-square data patterns.

symmetrical, asymmetrical

When comparing groups using a quantitative DV, - is used when the same participants are in both IV conditions, - is used when different participants are in the 2 iv conditions.

wg anova, between groups anova

- group comparisons include the same participants in all IV conditions, while - group comparisons involve different participants in each IV condition.

within, between

- groups anova is used for a longitudinal or repeated measures design, while - groups anova is used for a cross-sectional design.

within, between