Research Inferential Stats
Home > Flashcards > Print Preview
The flashcards below were created by user
on FreezingBlue Flashcards
. What would you like to do?
Inferential statistics are based on the laws of ____________ and are used to estimate population ________ from sample _________
Given data from a sample, inferential stats allows us to _______________
Draw conclusions or make inferences about a population
Different researchers applying inferential statistics to the same data are likely to draw __________ conclusions.
Inferentials stats assume _______ sampling from populations, assumption that is widely violated.
________ is the tendency for statistics to fluctuate from one sample to another.
_________ is a theoretical distribution of a statistic, using the values of the statistic (the means) computed from an infinite # of samples as the data points in the distribution.
What is a sampling distribution theoretical?
It is not actual because in practice no one draws consecutive samples from a population and plots their means.
When a distribution is normal _____ % of values fall between +, - 1 SD from the mean, _____ % fall between =, - 2 SD and _______ fall between =, - 3 SD's..
The standard deviation of a sampling distribution of the mean is called ________
standard error of the mean (SEM)
The___________ is an estimate of how much sampling error there is from one sample mean to another.
If we increase our sample size, we ________ the accuracy of our estimates.
Statistical inference consists of two techniques: ________ and ____________.
- estimation of parameters
- hypothesis testing
____________ is used to estimate a parameter
Examples of parameters are:
- a mean
- a proportion
- a mean difference btw groups
Estimation can take two forms:
- 1. point estimation
- 2. interval estimation
__________ involves calculating a single descriptive statistic to estimate the population parameter.
__________ estimation is useful because it indicated a range of values within which the parameter has a specified probability of lying.
The ___________ is the range of values within which a population parameter is estimated to lie, at a specified probability (e.g., 95 %__)
Confidence Interval (CI)
Confidence intervals reflect the researchers' _____________
risk of being wrong.
With a 95% CI, researchres aceept the probability that they will be wrong ____ times out of 100. A 99% CI, sets the risk of being wrong at _____.
For proportions based on dichotomous variables (positive or negative for a disease), the theoretical distribution is ___________
________ states that there is no relationship among the variables; that any findings are due to chance.
A _________ error means that the Null Hypothesis was rejected, when in fact it was true.
*"False positive". We said there was a difference/effect when in fact, there was not.*
A ______ error is made when researchers accept the null hypothesis when it fact it was NOT true.
This is a "false negative" conclusion. We said there is no difference, when in fact one exists.
A ________ error might prevent a good drug from coming to market.
A_________ error might allow an ineffective drug to come onto the market, while a
How do researchers control the risk of a Type 1 error?
By selecting a level of significance, which signifies the probability of incorrectly rejecting a true null hypothesis.
What is alpha?
Level of significance. Usually .01 or .05.
With a .05 alpha level, what is the risk of us incorrectly rejecting the null hypothesis?
5 out of 100 chance.
Lowering the risk of a Type 1 error can increase___________
the risk of making a Type 2 error.
The simplest way of reducing the risk of a Type 2 error is to ___________.
Increase sample size
Levels of significance are analogous to _____.
Whereby alpha of .05 =_______
What does the word significant mean in statistics?
Obtained results are not likely to be due to chance, at a specified level of probability.
What does a non-significant result mean?
An observed result could reflect chance fluctuations.
A one-tailed test would be best when a ________ hypothesis is strongly suspected.
There are two broad classes of statistical tests.
Parametric and Nonparametric
________ tests involve estimation of a parameter, require measurements on at least an interval scale and involve several assumptions, such as the assumption that the variables are normally distributed in the population.
__________ tests, do not estimate parameters; they involve less restrictive assumptions about the shape of the variables' distribution than do __________
When the N is> 50, it may not be necessary to use ___________ statistics, unless the population has a markedly unusual distribution.
What is the central limit theorem?
A statistical principle stipulating that the larger the sample, the more closely the sampling distribution of the mean will approximate a normal distribution and the mean of a sampling distribution equals the population mean.
When comparisons involve different people (men versus women), the study uses a _________ design and the statistical test is a ____________.
- Between-subjects design
- Test for Independent groups
__________ statistical tests are used when there is only one group, that is used in multiple conditions (cross-over designs).
Tests for dependent groups
What are the steps for testing a hypothesis?
- 1. Select the appropriate test
- 2. Establish the level of significance
- 3. Select a 1-tailed or 2-tailed test.
- 4. Compute a test statistic
- 5. Determine the degrees of freedom
- 6. Compare the test stat with a tabled value.
________ refers to the # of observations free to vary about a parameter.
Degrees of Freedom.
What is the parameter procedure for testing differences in group means?
What is an adjustment made to establish a more conservative alpha level when multiple statistical tests are being run from the same data set.
When means for two sets of scores are not independent (dependent), researchers should use________
a paired t-test
VandeVusse et al. used ______ to assess changes in women's HR, RR and tensoin anxiety following exposure to a 30 min self-hypnosis intervention.
In certain 2 group situations, a non-parametric test may be needed. Two examples/reasons to use a non-parametric test are_____,_______
- 1. if the dependent variable is on an ordinal scale
- 2. If the distribution is markedly non-normal.
The _________ test is the non-parametric analog of an independent group's t-test and involves assigning ranks to the two groups of scores. The sum of the ranks for the 2 groups can be compared by calculating the ____ statistic.
When ordinal level data are paired (dependent), the ________ test can be used. This test involves taking the difference between paired scores and ranking the absolute difference.
_______ is the parametric procedure for testing differences between means when there are 3 or more groups by comparing variability between groups to variability within groups.
The statistic computed in ANOVA tests is _______
What would you like to do?
Home > Flashcards > Print Preview