Null Hypothesis correct answers Assumes the two variables have no meaningful relationship, only little bits of association that tend to appear at random.
Alternative Hypothesis correct answers There are important differences in one variable as another variable changes, and we only really believe...
BBH 310- Exam #2 Prep || Questions and 100% Verified
Answers.
Null Hypothesis correct answers Assumes the two variables have no meaningful relationship,
only little bits of association that tend to appear at random.
Alternative Hypothesis correct answers There are important differences in one variable as
another variable changes, and we only really believe differences are real if they are larger than
what we would often expect to see just by luck.
False positive, or a Type 1 error correct answers Incorrectly detecting the disease when the
patient really does not have it.
False negative, or Type 2 error correct answers Failing to detect the disease when the patient
really has it.
Type I Errors correct answers -alpha is high
-many variables are tested or many separate tests are done over and over
Type II Errors correct answers -Sample size is small
-Variability is high
-Effect of predictor variable on outcome variable is weak
-Alpha is very small
Unstandardized Effect Size correct answers Describes the size of an effect in the units of the
variables of interest.
Standardized Effect Size correct answers Takes into account the amount of variability, usually
measured by standard deviation, in the data at hand. You might remember from a previous stats
class that when you standardized a variable (creating Z scores) you divided the difference from
the mean by the standard deviation, and this involves the same process.
Statistically Significant correct answers Based on a basic statistical analysis, the results appear to
be unlikely to have emerged by chance under the null hypothesis, with p < alpha.
Clinically Significant correct answers Results directly matter to the practice of medicine; they
have important and readily noticeable effects on a person's health.
A drug doesn't work. But a pharmaceutical company keeps running studies different ways until
finally, one study gets a significant benefit of the drug. They hide the results of the non-
significant studies, and only publish the significant results for everyone to see. The result they
publish is a : correct answers False positive finding, indicating that their way of doing research is
not-specific enough to only find results of drugs that really work
, If we set our alpha level (cutoff between significant and non-significant) at 0.05 and run 40
studies on a drug that doesn't work, how many false positive findings should we expect?
Group of answer choices correct answers 2
-Expected false positive rate, given that the null hypothesis is true (drug doesn't work), is equal
to alpha times the number of tests. 40*.05 is equal to 2. Hopefully, you can do that math without
a calculator, either by actually taking 4 times 5 to get 20 and then moving the decimal place two
to the left because the 5 is the hundredths place and one to the right because the 4 is in the tens
place, or by recognizing that .05 is equal to 1/20, and 40/20 = 4/2 = 2. We won't ask you to do a
lot of math, but simple operations with .05 and .01 is going to be a common theme, so do
memorize the 1/20 trick, that makes it really easy.
Imagine we have a drug that does help lower blood sugar, but it only helps a little bit, and it
doesn't work for everyone. The researchers are scared of type 2 errors. They come up with a list
of things that they should do to reduce the risk of type 2 errors. Which reason does not belong on
the list, because it will actually increase the risk of type 2 error? correct answers Reduce the
significance threshold alpha
-As the lesson discussed, large sample size reduces risk of type 2 error. Furthermore, reducing
variability in the measure also reduces risk of type 2 error. However, when alpha gets small, it's
INCREASING the risk of type 2 error (because it's harder to get a significant finding at a more
stringent threshold).
Correlation correct answers A measure of the strength and direction of association that exists
between two variables measured on at least an interval scale.
-This is used if both variables are quantitative
Chi squared test correct answers A statistical hypothesis test that is valid to perform when the
test statistic is chi-square distributed under the null hypothesis,
-This is used if both variables are categorical
T-test or ANOVA correct answers Determines whether two populations are statistically different
from each other
OR
Determines whether three or more populations are statistically different from each other.
-This is used if one variable is categorical and the other is quantitative
Which statistical test do you think would be appropriate for a clinical trial testing a drug against
a placebo, where the outcome of interest is the number of cigarettes smoked in the last week of
the trial? correct answers T-test
The t-statistic in a T-test approximately represents: correct answers How many standard errors
apart are two means
The p value in a chi-squared test indicates the probability that under the null hypothesis, there
would be at least as much difference between: correct answers The probability of being in certain
categories of variable A depending on which categories of variable B the subjects were in
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