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Math
Statistics
BOARDS: Research 2
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Terms in this set (51)
conditions that are imposed to keep groups of individuals from knowing which subjects have or have not received an intervention
blinding:
single
double
triple
group against which the treatment group is compared, statistically identical to the treatment group, except for the variable of interest that is being evaluated
control group:
1. active-known effective form of treatment in a clinical trial against which the experimental treatment is compared. Unethical to use placebo in this case
2. placebo
identify pairs of subjects who have identical characteristics (weight, age, race)
matching/pairing
all subjects randomly assigned to one of the treatments are analyzed together, regardless of whether they received or completed that treatment
intention to treat analysis
degree to which results of the research study are generalizable to populations or circumstances beyond those included in the study
external validity: threats include specific type of subjects place, time
degree to which an intervention being evaluated is the cause of the outcome measured
internal validity
assigning subjects to groups in an experiment so that each subject has an equal chance of being assigned
randomization
tendency of individuals to change their behavior in response to the fact that they are being observed or studied
hawthorne effect
inactive treatment or procedure that is intended to mimic a real treatment causes an improvement
placebo
also known as the experimental hypothesis; statement that the population parameter as value that differs from the null hypothesis ; accepted when null is rejected
alternate hypothesis
also known as the statistical hypothesis; statement that the value of a population parameter is equal to some claimed value
null hypothesis
variable caused or influenced by dependent variable and is controlled or manipulated by researcher
independent variable
variable that is the response or outcome
dependent variable
probability that a particular statistical result could have happened by chance
p-value
when the p-value is smaller than the stated value of alpha, or level of significance, the null hypothesis is
rejected
when the p-value is larger than the stated value of alpha, or level of significance, the null hypothesis is
no rejected
also known as the significance level, probability of rejecting the null hypothesis when it is true, or the chance of committing a type 1 error
alpha level (traditional values are .05 and .01)
- .01 alpha level means that you leave open a 1% possibility of being wrong if you reject the null hypothesis (which is kinda sorta simplifiable to a 99% chance that the alternate/research hypothesis is "correct"). If the alpha level is .05, there's a 5% chance of being wrong if you reject the null.
error when wrongly deciding to reject the null, concluding there is a difference or relationship when there is not
type 1 (alpha) error
error when wrongly deciding not to reject the null, concluding that there is no difference or relationship when there is.
type 2 (beta) error
a type 1 error is a
false positive
-error when wrongly deciding to reject the null, concluding there is a difference or relationship when there is not
a type 2 error is a
false negative
-error when wrongly deciding not to reject the null, concluding that there is no difference or relationship when there is.
probability is small that the difference between groups or the relationship between variables happened by chance
statistically significant
chance that a statistical test will lead to rejection of a false null hypothesis
statistical power
measure of the magnitude of the difference between two treatments or the magnitude of the relationship between two variable, larger the more likely it will be statistically significant
effect size
the larger the effect size, the more likely it will be
statistically significant
smallest difference in a patient's condition that the patient or clinician considers worthwhile and that would, in the absence of side effects and excessive cost, warrant a change in the patient's management
MCID
minimum detectable change in the pt's condition beyond the threshold of measurement error, smallest difference or change that would be statistically significant
MDD
type of graph used to show the magnitude or frequency of categories of the data
bar
type of graph that illustrates the distribution of values whiten a group through five numbers
box and whisker plot
graph used in a meta analysis that shows the results of the individual studies as well as a cumulative summary of all studies
forest plot
-width of squares in horizontal line represent confidence intervals
-diamond represents the measure of effect for all studies combined
graphical display of a frequency distribution; frequency on y axis for each interval represented on the x axis
histogram
graph that demonstrates the relationship between two or more quantitative variables; dependent variable on y and independent on x
line graph
graph that illustrates the relationship between two quantitative variables
scatter plot
graphical display which enables the reader to observe the entire distribution of data without losing any information
stem and leaf plots
on a bell curve:
a. approximately __% of all values fall within one standard deviation above and below the mean
b. __% fall within 2 SDs
c. __% fall within 3 SDs
a. 68%
b. 95%
c. 99%
In a negatively skewed distribution on a bell curve, the median and mean are to the ___ of the mode and that tail is elongated
left (on a positively skewed distribution, the mean and median are to the right of the mode and the right tail is elongated)
_____ statistics assume that samples come from populations that are normal distributed
a. parametric
b. nonparametric
a.
5 types of parametric statistics
1. ANOVA
2. T test
3. z test
4. Confidence intervals (CI)
5. Correlation
inferential parametric statistics procedure used to test the quality of means between two or more populations
ANOVA
-One way analysis of variance: one independent variable
-Two way analysis of variance: 2 or more IVs
-Repeated measures analysis of variance: measured under a number of different experimental conditions
-Regression analysis: predicts how a change in one or more of the IVs affects the DV
range of values used to estimate a population parameter, also known as the interval estimate
confidence interval
probability, usually expressed as a percentage, that the confidence interval actually contains the unknown population parameter
confidence level
(95% confidence level means that if the same population is sampled 100x and CIs are calculated on each sample, 95 of the resulting CIs would be expected to contain the true population parameter)
single value calculated from a sample that best approximates a population parameter of interest
point estimate (sample mean is the point estimate for the mean of the population)
statistical measure of the strength association among two or more variables
Correlation
-Intraclass correlation (ICC): assesses both degree of correspondence and agreement among scores; 0-1
-Pearson product moment correlation (r ): -1.0 and +1.0 with + meaning the two variables increase or decrease together;- means an increase in one is associated with a decrease in the other.
inferential statistical procedure for estimating a population mean or comparing two means when the population is normally distributed and the population variance is not known
t-test
-one tailed: intervention could have only one effect (beneficial or harmful)
-two tailed (test statistic is symmetrically distributed)
statistical procedure for estimating the mean of a population or comparing two means when the population is normally distributed and the population variance is known
z-test
when referring to a medical test _____ refers to the percentage of people who test positive for a specific disease among a group of people who have the disease
sensitivity
when referring to medical test, ____ refers to the percentage of people who test negative for a specific disease among a group of people who do not have the disease
specificity
test that indicates a person does not have a specific disease or condition when the person actually does have the disease or condition
false negative test
test that indicates a person has a specific disease or condition when the person actually does not have the disease or condition
false positive test
SpPin
High specificity value and the confidence we have in ruling in the diagnosis
In a test with high specificity, a positive diagnostic test rules in the diagnosis
SnNout
high sensitivity value and the confidence we have in ruling out the diagnosis
In a test with high sensitivity, a negative diagnostic test rules out the diagnosis
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A peony plant with red petals was crossed with another plant having streaky petals. The probability that an offspring from this cross has red flowers is .75. Let x be the number of plants with red petals resulting from ten seeds from this cross that were collected and germinated. a. Does the random variable x have a binomial distribution? If not, why not? If so, what are the values of n and p? b. Find P(x$\geq$9). c. Find P(x$\leq$1). d. Would it be unusual to observe one plant with red petals and the remaining nine plants with streaky petals? If these experimental results actually occurred, what conclusions could you draw?
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