Intermediate statistics 1
Intermediate Statistics I (advanced) 2025
Exam based questions and approved answers
Accuracy - ✔✔✔describes how close the samples are to the true value of the population.
Dependent variable - ✔✔✔the outcome variable and is the variable that is not manipulated
by the experimenter
One tailed test - ✔✔✔you test the hypothesis in one direction (the parameter is larger/smaller
than the parameter specified in the null hypothesis)
Accuracy can be improved - ✔✔✔through randomization (random sampling).
Precision - ✔✔✔describes how disperse the individual observations are from each other. It is
a way to determine the variance or noise in the data
Precision can be improved - ✔✔✔increasing sample size
Alpha - ✔✔✔is the probability of rejecting the null hypothesis when the null hypothesis is
true (i.e. the probability of a Type I error). Exogenously determined threshold, beyond/below
which obtained results are deemed to be statistically significant - probability of making a
Type I error
Beta - ✔✔✔the probability of making a type II error
@ pg. 1
, Intermediate statistics 1
Type I error - ✔✔✔is the incorrect rejection of a true null hypothesis (false positive).
Type II error - ✔✔✔failure to reject a false null hypothesis (false negative).
Effect size - ✔✔✔d= (M1-M2)/s
Cohen’s - ✔✔✔is defined as the difference between the means of the H0 distribution and the
Ha distribution. Small is 0.2, medium is 0.5, large is 0.8, very large is 1.3.
Statistical power - ✔✔✔is the probability that your study will find a statistically significant
difference between interventions when an actual difference does exist (sensitivity). If (...) is
high, the likelihood of deciding there is an effect, when one does exist, is high
Increase statistical power - ✔✔✔Increase alpha. Increasing the significance threshold means
that the rejection region gets larger, thus increasing the probability that a true effect is
actually classified as such. Reducing measurement/random error by using more reliable and
accurate measures and/or collecting data of higher quality. This allows for greater precision
of sample estimates, and therefore tighter H0 and Ha sampling distributions. Increase N. By
the law of large numbers, increasing N increases the precision of our sample estimates. This
works to reduce any overlap between the H0 and Ha distributions, thus increasing power
Histogram - ✔✔✔is a graph plotting values of observations on the horizontal axis, and the
frequency with which each value occurs in the data set on the vertical axis. Ratio and interval.
Two tailed test - ✔✔✔you test the hypothesis in both directions (the parameter is larger
and/or smaller than the one specified in the null hypothesis)
@ pg. 2
Intermediate Statistics I (advanced) 2025
Exam based questions and approved answers
Accuracy - ✔✔✔describes how close the samples are to the true value of the population.
Dependent variable - ✔✔✔the outcome variable and is the variable that is not manipulated
by the experimenter
One tailed test - ✔✔✔you test the hypothesis in one direction (the parameter is larger/smaller
than the parameter specified in the null hypothesis)
Accuracy can be improved - ✔✔✔through randomization (random sampling).
Precision - ✔✔✔describes how disperse the individual observations are from each other. It is
a way to determine the variance or noise in the data
Precision can be improved - ✔✔✔increasing sample size
Alpha - ✔✔✔is the probability of rejecting the null hypothesis when the null hypothesis is
true (i.e. the probability of a Type I error). Exogenously determined threshold, beyond/below
which obtained results are deemed to be statistically significant - probability of making a
Type I error
Beta - ✔✔✔the probability of making a type II error
@ pg. 1
, Intermediate statistics 1
Type I error - ✔✔✔is the incorrect rejection of a true null hypothesis (false positive).
Type II error - ✔✔✔failure to reject a false null hypothesis (false negative).
Effect size - ✔✔✔d= (M1-M2)/s
Cohen’s - ✔✔✔is defined as the difference between the means of the H0 distribution and the
Ha distribution. Small is 0.2, medium is 0.5, large is 0.8, very large is 1.3.
Statistical power - ✔✔✔is the probability that your study will find a statistically significant
difference between interventions when an actual difference does exist (sensitivity). If (...) is
high, the likelihood of deciding there is an effect, when one does exist, is high
Increase statistical power - ✔✔✔Increase alpha. Increasing the significance threshold means
that the rejection region gets larger, thus increasing the probability that a true effect is
actually classified as such. Reducing measurement/random error by using more reliable and
accurate measures and/or collecting data of higher quality. This allows for greater precision
of sample estimates, and therefore tighter H0 and Ha sampling distributions. Increase N. By
the law of large numbers, increasing N increases the precision of our sample estimates. This
works to reduce any overlap between the H0 and Ha distributions, thus increasing power
Histogram - ✔✔✔is a graph plotting values of observations on the horizontal axis, and the
frequency with which each value occurs in the data set on the vertical axis. Ratio and interval.
Two tailed test - ✔✔✔you test the hypothesis in both directions (the parameter is larger
and/or smaller than the one specified in the null hypothesis)
@ pg. 2
