Chapter 9 Flashcards
What are the 2 types of inferential techniques?
Hypothesis testing and interval estimation are two inferential techniques
that are based on the concept of random sampling distributions.
What is a priori and post hoc?
In hypothesis testing, we have an a priori (before the fact) hypothesis about
the value of some parameter or the relationship between parameters.
Interval estimation, then, is a post hoc (after the fact) technique
What is confidence interval?
A range of values computed from sample data within which a parameter of interest has a known probability of falling.
Usually 95% or 99%
These two values, ±1.96 and ±2.58, are called _______ in inferential statistics.
These two values, ±1.96 and ±2.58, are called critical values in inferential statistics.
What is a critical value?
Critical value: The value of a statistic corresponding to a given significance
level determined by its sampling distribution.
Differentiate between conceptual and alternate hypothesis.
A conceptual hypothesis is a statement about the relationship between theoretical concepts. Examples include “Punishment facilitates learning.”
A research hypothesis is a statement about the expected relationship between
observable or measurable events.
Conceptual hypotheses can be directly tested. True or false?
They can never be directly tested because they are not measurable as defined.
Conceptual hypotheses must be operationalized or made measurable before we can test them.
What are the types of research hypotheses, and what are the statements they would make?
An experimental research hypothesis
states expected relationships between independent and dependent variables.
For example, “Shock, following errors, will decrease the number of errors
made.”
A correlational research hypothesis states the expected relationship between two or more variables. “The lower the income, the higher the number of convictions.”
What is a statistical hypothesis?
A statistical hypothesis states an expected relationship between numbers that
represent statistical properties of data
“The mean number of errors is
the same under shock and no-shock conditions.”
Differentiate between null and alternate hypothesis.
The statistical hypothesis includes the hypothesis that one wishes to disprove (the null hypothesis) and the hypothesis that one wishes to confirm (the alternative hypothesis).
Differentiate between a directional and non-directional hypothesis.
An alternative hypothesis that negates the null is called a non-directional alternative.
It is called a directional alternative if it specifies the direction of the difference.
What are the assumptions made about z tests for independent means?
Assumptions
- Participants are randomly selected and independently assigned to groups.
- Population distributions are normal.
- Population standard deviations are known.
When do we reject and fail to reject the null hypotheses?
Reject hypotheses if the z obtained is equal to or greater than the critical value.
Fail to reject if the z obtained is less than the critical value.
Differentiate between type 1 and type 2 error.
Type I error is a false positive
* When the null (H0) is correct, we would falsely reject it (and
accept H1) 5% of the time → false positive
* Probability of Type I error is ɑ
* Reduce ɑ to lower Type I error (.05 → .01)
Type II error is a false negative
* When the null (H0) is false, but we fail to reject it (and do not
accept H1) → false negative
* Probability of Type II error is 𝞫
* Reduce 𝞫 to lower Type II error
The higher the false positive, the lower the false negative. True or false?
True. The higher the ɑ the lower the B
To reduce the probability of making a Type II error, we need to increase the
alpha level (e.g., from .01 to .05).
