Midterm Flashcards
What type of variable is temperature (degrees F)?
Interval
What type of variable is femur length (cm)?
Ratio
What type of variable is metastases occurrence (yes or no)?
Nominal
What type of variable is pain intensity (1-10)
Ordinal
Which measure best describes the variation within your sample?
Standard deviation
Which of the following is (are) true of a normal distribution?
- It has a central tendency
- About 68% of its variation is found within one standard deviation from the mean
You have twenty mice in your lab: 10 male (8 with white fur, 2 with brown fur) and 10 female mice (3 with white fur, 7 with brown fur). You suspect fur color might be an X-linked trait (i.e. a relationship between sex and fur color).
State the null hypothesis.
The null hypothesis is that fur color is not an X-linked trait (i.e. there is no relationship between sex and fur color).
I believe amphetamine will increase anxiety in a certain transgenic mouse model. I measure anxiety as the time (in sec) it takes the mouse to move into the central portion of an open field arena with lower movement times interpreted as less anxiety. I measure movement time in one group of mice following amphetamine injection and a second group of mice following injection of a control substance.
What is the null hypothesis?
The null hypothesis is that amphetamine will not increase anxiety in a certain transgenic mouse model meaning that the mouse will move into the central portion with lower movement times.
I test the null hypothesis that a ginseng pre-treatment does not affect alcohol-induced loss of balance in comparison to a control group. I conclude that ginseng has no effect, when it actually does.
Identify which type of error (Type I or Type II) or non-error being made here.
Type II, false negative
I test the null hypothesis that there is no association between eye color and genetic sex (XX, XY, etc.). I conclude that there is no relationship between eye color and sex when in fact there is not.
Identify which type of error (Type I or Type II) or non-error being made here.
No error, fail to reject true null hypothesis
During a drug screening for professional athletes, the null hypothesis is that there is no drug use. A drug test detects the presence cannaboids in the urine and the athlete admits to their use of marijuana.
Identify which type of error (Type I or Type II) or non-error being made here.
No error, reject false null hypothesis
As a juror, my null hypothesis is that the defendant is innocent until proven guilty. I conclude that the individual on trial is guilty when in fact she is not.
Identify which type of error (Type I or Type II) or non-error being made here.
Type I, false positive
When is it appropriate use a one-tailed test vs. a two-tailed test?
If you need directionality in one direction you apply a one-tailed test (i.e. positive direction), if you need directionality in both directions you apply a two-tailed test (i.e. positive and negative direction). Additionally, a two-tail test is appropriate when the null is stated as equal to a value while alternative states the test is not equal to the value.
In relation to statistical hypothesis testing, define alpha (α).
Alpha in relation to statistical hypothesis testing represents a false positive. Furthermore alpha is the level of significance, 1 - the confidence level, and the probability of a type I error.
In relation to statistical hypothesis testing, define beta (β).
Beta in relation to hypothesis testing is a false negative and the probability of a type II error. Furthermore 1-beta represents the power of a test.
In relation to statistical hypothesis testing, what is a Bonferroni correction? How is it related to alpha and beta?
Bonferroni correction is used when there is a multiple statistical tests being run simultaneously. A Bonferroni correction will decrease the alpha and increase the beta.
Define probability
Probability is a mathematical tool used to study randomness. It deals with the chance (the likelihood) of an event occurring.
Define descriptive studies
Descriptive statistics are used to describe or summarize the characteristics of a sample or data set, such as a variable’s mean, standard deviation, or frequency. Also known as “what is” or correlations.
Define experimental studies
Experimental studies are ones where researchers introduce an intervention and study the effects. Experimental studies are usually randomized, meaning the subjects are grouped by chance. Also known as “what if” or causation. Does the treatment affect the observation?
Define correlation vs causation
A correlation is a statistical indicator of the relationship between variables. Causation means that changes in one variable brings about changes in the other; there is a cause-and-effect relationship between variables.
Define experimental validity
Experimental validity refers to the manner in which variables that influence both the results of the research and the generalizability to the population at large.
Define internal validity
Internal validity is defined as the extent to which the observed results represent the truth in the population we are studying and, thus, are not due to methodological errors. Is the effect actually due to the manipulation?
Define external validity
External validity is the extent to which you can generalize the findings of a study to other situations, people, settings and measures. Is the effect unique to your experiment or generalizable?
List the threats to internal validity
- History (unrelated event occurring between 2 measures ex: power outage in the animal’s enclosure, stresses them out)
- Maturation (processes within subjects which act as a function of the passage of time ex: First measurement occurs just after birth, second taken months later)
- Testing (effects measuring study outcomes in participants ex: Post-test scores improves due to exposure to pre-test, not treatment)
- Instrumentation (changes in the instrument, observers, or scorers which may produce changes in outcomes ex: PI measures respiration rate immediately after putting a mouse in the chamber, research assistant waits 5 minutes then records respiration rate)
- Statistical regression (Regression to the mean
ex: Measuring pain levels before and after treatment) - Selection of subjects (the biases which may result in selection of comparison groups ex: Control group consists of older males, treatment is younger females)
- Experimental mortality (the loss of subjects ex: Human subjects leave study, mice die)