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75 Cards in this Set

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Null hypothesis
implies that there is no relationship between the independant and dependant variables. Any effects are due to sampling error.
Alternative hypothesis
implies tha there is a relationships between the independant and depednent variables
alternative hypothesis can be either _________or ______
non directional or directional
Non directional
Just states that the null hypothesis is false
one directional (one tailed)
not only states that null hypothesis is false but also predicts whether the population parameter estimated by the obtainedsample statistic will be greater or less than the parameter speficied in null hypothesis
rejection region
lies in one or both tails of samping distruibution and contains the sample values that re UNLIKELY to occur simply as a result of a sampling eorr. If statistical test indicate that the sample statistic is in the rejection regoin of the sampling distriubution, the null hypothesis is rejected and the alternative hypothesis is retained.
Retention region
lies in the central portion of the sapling distrubution and consists of the values that are more likely to occur. . If the sample statistic lies in the rention region, the null hypothesis is retained and the alternative hypothesis is rejected.
Alpha (level of significance)
size of rejection region is defined by alpha. if alopha is .05 then five percent of the sampling distribution represents the rejection region and the 985 percent represents the retention region. it is set by the investigator prior to collecting and or analyszing the data.
statistically significant
when results of inferential statistical test indicate that the sample statistic lies in the rejection region of the sampling distribution.
type one error
occurs when an investigator rejects a true null hypothesis . probability of making at type one error is set at alpha
Type II error
occurs when an investigator retains a false null hypothesis
correct decisions
retain null hypothesis when it is true or rejectin null hypothesis when it is false
Power
when the decision is made to reject a false hypothesis
parametric test
used to evaluate hypothesis about population means variances or other parameters. appropriate when the variable of interest are measured on the interval or ratio scale and when certain assumptions about the popuation are met

Interval ratio data all t-test
one way anova
factoraila anova
Assumption one
the value of interst is normally distributed in the population
assumption 2.
when a study includes more than one group, the cariances of the populations that the different groups represent are assumed to be equal (homoscedasity, refers to equal variances).
non parametric tests
used to analzyze data on variables that are measured on nominal or ordinal scale. Evaluates hypothesis about the shape of the entire distribution rather than the distribution mean's variance or other parameter. Less powerful. ARe less likely to reject a null hypothesis with a non parametric test. Parametric test are preferred
Critical value.
used to compare the test statistic that is resulted from a inferentail statistical test (non par or par). if the test equals or exceeds the critical value, the investigator concludes that the obtained sample value lies in the rejection region and the samping distribution and rejects the null hypothesis. if the test statistic is less than the critical value then the rsearcher concludes the sample value lies in the retention region and retains the null hypothesis
degrees of freedom
are niumber of values or categories that are free ot vary given the certain values or categories in the distributions are known or fixed.
Magitude of critical value depends on what two factors
level of significance and degrees of freedom
assumption 2.
when a study includes more than one group, the cariances of the populations that the different groups represent are assumed to be equal (homoscedasity, refers to equal variances).
non parametric tests
used to analzyze data on variables that are measured on nominal or ordinal scale. Evaluates hypothesis about the shape of the entire distribution rather than the distribution mean's variance or other parameter. Less powerful. ARe less likely to reject a null hypothesis with a non parametric test. Parametric test are preferred
Nominal data: Single sample chi square, Multible sample chi square
Ordinal data: wilcoxon matched pairs test , mann whitney u test
kruskal wallis test.
Critical value.
used to compare the test statistic that is resulted from a inferentail statistical test (non par or par). if the test equals or exceeds the critical value, the investigator concludes that the obtained sample value lies in the rejection region and the samping distribution and rejects the null hypothesis. if the test statistic is less than the critical value then the rsearcher concludes the sample value lies in the retention region and retains the null hypothesis
degrees of freedom
are niumber of values or categories that are free ot vary given the certain values or categories in the distributions are known or fixed.
Magitude of critical value depends on what two factors
level of significance and degrees of freedom
single sample chi test
when a descriptive study includes one variable and the data to be analyzed are the number of observation in each category: one variable nominal frequency data
multipl,e sample chi square test
used when descriptive or expereimental study includes two or more variables and the data to be abalyzed are the number of observations in each category: two or more variables: nominal data
student's t- test
used to evaluate hypothesis about the differences between two popuation means as estimated by group means. used to analyze data collected from more than two groups.
Student's t-test for single sample:
used when a study includes only one group and the mean obtained by that group will be compared to a population mean. one indepedendant variable single group. One dependant variale, interval or ratio data
student's t-test for independant sample
is appropraite statistical test when a study includes two independant groups. one independant variable, two independent groups. one dependent variable interval or ratio data
Student's t-test for correlated samples
t- test for correlated samples is used when the two means to be compared have come from correlated groups.for exaple a study using within subject design in which a single group of subjects will be compared to itself. or when subjects are matched on extraneous variable and members of each matched pair have been assigned to different groups.
Anova
is used to compare two or more more means. It tests hypothesis that the populatio means estimated by the group means are equal.
One way anova.
appropriate statistical test when a study includes one independant variable and two or more independent groups. LIke the t0test, the anova compres means but does more complex way by analyszing variablity around the means. one indepedent variable, two or more indepednt groups one dependent variable, interval or ratio data
Factorial, analysis of variance
appropriate statistical test when a stuy includes two or more independant variables. Two ivs: two way anova. two or more independent variables , independent groups .One dependnt variable interval or ratio data.
regression analysis
assumption underlying regression analysis is that there is a linear relationship between the two varaibles of interst and therefore, that the relationship can be sumarized by a straight line: the relation ship can be sumarized by a straight line, and the relationship can be described by a regression line or line of best fit.
longitudinal studies
investigate changes by assessing the same group of people over an extended period of time. Overcome the problem of cohort effects but difficult to conduct because of time and cost factors and subject to high drop out rates
Cross sequential studies
combines cross-secttional studies and longitudinal methodologies by asessing member of two or more age groups at two or more different times.
Evaluation research
conducted to assess the value or effectiveness of psychological educational and other social programs.
Extraneous variable
irrelevant to the purpose of a research but counfounds the study's results because it has a systematic effect on the dependant variable
Control extraneous variables
1.random assignment of subjects to a treatment group
2.hold extraneous varaible constant (selecting subjects who are homeogenous wiht the respect to that variable)
3. Match subjects on teh extraneous variable (match subjects with that variale then randomly assign matched subjects to one of the treatment groups.)
4. building extraneous variable into the study (include as independant variable)
5. Satistical control of the extraneous variable
(ancova) or other statistical tecniques to remove varaiblity in the dependant variable.
Threats to internal validity
1.maturation
2. history
3.testing
4.instrumentation
5. statistical regression
6.selection
7. attrition (mortality
Threats to external validity
1. interaction between testing and treatment. When administration of a pretest can sensitize subjects
2. interaction between selection and treatment. (volunteers are different from non volunteers.)
3. Reactivity: Reacting a particular way just because you know you're being observed . Hawthorne effect, evaluation apprehension, demand characteristics
4.multiple treatment interference. Occurs when exposed to several levels of treatment.
Hawthorne effect
tendenct of subjects to perform better because the attention they are recieving as research partcipants
Evaluation apprehension
causes subjects to act in ways they believe will help them avoid negative evaluation
Demand characteristics
behavior or research participants can be altered by cues that inform the subjects of the purpuse of the study or suggest what behaviors are expected of them
Experimenters expectancy
Can unintentionally provide subjects with cues
Between group designs
Administer different levels of independant variable are administered to diffent groups of subjects and then comparing the status or performance of the groups on the dependant variable.
within subjects designs
all levels of the independant variable are administered at differnt times to all subjects
comparisons are made within subjects rather than between groups of subjects
Mixed designs
combines between groups and wihtin subjects methodology
counterbalanced deisngs
mixed desings because they permit comparisons both between groups and within subjects
Single subject designs
Inclue at least one base line phase and one treatment phase. subjects act as their own no treatment controls
AB design
single baseline and single treatment phase
ABA, ABAB design
requires withdrawl of the treatment during second and subsequent baseline phases. Reversal or withdrawl design
multiple baseline desgn
does not require the withdrawl of a treatment during the course of the study . involves sequentially applying the treatment to different behaviors of the same subject, to the same subject in differtn setting
to the same behavior in differnt subjects .
Nominal scale
divides varibales into uordered categories
sex of people. eye color, polititical affliation
Ordinal scale
divides observations into categories and provides information on the order of the category. Use of rating scales
Interval scale
property of order as well as the property of equal intervals betwen successive points on the measurement scale
Ratio scale
properties of order , equal intervals and property of an absolute zero point. Score of zero indicates a complete absence
Kurtosis
relative peakness of a distribution
Lptokurtic
distribution is more peaked then the normal curve
Platykurtic
Distrubution is flatter than the normal curve
Mesokurtic
normal cuve
Postively skewed distribution
most of the scores are in the negative side of the distribution. Positive tail is extended because of a presense of a few high scores
Negatively skewed distribution
most scores are on positive side with the tail being in the negative
Mode
score or category that occurs most frequency in a set of data
median
score that divides the distribution of data in half when data have been ordered from low to high. Equal to the middle observation
Arithmetic mean
average .summing all values and dviding the sum of of values in the distibution
Choosing a measure of central tendency for nominal, ordinal ,interval and ratio
Nominal: mode
Ordinal: mode or median
Interval and ratio: mode, median or mean
Meausres of variablity
1. range
2. Variance
3. standard deviation
Range
caluculated by subtracitng the lowest score in the distribution from the higher score. can be misleading if there is a really high score or really low score that is not typical
Variable
provides measure of average amount of varaiblity in the distribution. Includes all the scorews in distribution. variance requires squaring each deviation score . used in inferential statistics
Standard deviation
expressed in the same unit of measurement as original scores. Calculated by taking the square root of the variance
mann whitney U test
study inclues two independant groups and data on dependant variable are reported in terms of ranks. assesses whether or not the ranks of the observation in one group are equivielant to the ranks of obervations in the other group.
Wilcoxon matched pairs signed ranks test
when a study includes two correlated groups and the differences between the dependant variable scores are converted to ranks . assess whether or not there is a difference bewteen the sum of the ranks of the positive difference between socores and the sum of the ranks of the negative diffences between them
Kruskal wallis one way analysis of variance test
similar to man -whitney u test but used when a study includes two or more independnt groups . Test is used to assess the hypothesis that the ranks of observations in the differnt groups are equivant.