Midterm 1 Prep Flashcards

1
Q

What is the p-value?

A

The probability of observing a test statistic as or more extreme than the one we observed, given that 𝐻o is true.

A lower p-value indicates stronger evidence against the null hypothesis.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the Normal Distribution?

A

A Gaussian distribution, most used distribution in statistics.

It is characterized by its bell shape and symmetry about the mean.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

What does the Central Limit Theorem state?

A

Anything over 30~ is going to be normally distributed.

This theorem is fundamental in statistics as it justifies the use of normal distribution in many situations.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is a Sampling Distribution?

A

The set of all possible sampling statistics we could have in our sample or the collection of all possible Xbars from the population.

It describes how a statistic (like the mean) varies from sample to sample.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Define Type I Error.

A

Rejecting 𝐻o when 𝐻o is true, also known as a false positive, denoted as 𝛼.

This error can lead to incorrect conclusions about the effectiveness of a treatment or intervention.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Define Type II Error.

A

Failing to reject 𝐻o when 𝐻o is false, also known as a false negative, denoted as β.

This error occurs when a test fails to identify a difference or effect that truly exists.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is Alpha (𝛼)?

A

The significance level, critical region, and represents the probability of a Type I error.

Commonly set at 0.05 in many studies.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is Beta (β)?

A

The probability of a Type II error.

It represents the likelihood of failing to detect an effect when there is one.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What does Power mean in statistical terms?

A

1 - β = Power, indicating the probability of correctly rejecting the null hypothesis.

Power increases as sample size increases or effect size increases.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a Critical Region?

A

The set of values for a statistic that would lead to a rejection of 𝐻o.

It defines the threshold for significance in hypothesis testing.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is Paired Comparison (blocking)?

A

When two samples are NOT independent, with measurements on two units within a block.

This approach helps control for variability between the paired units.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What does Difference (δ) represent?

A

The difference between two treatment effects or group means.

It is often used in hypothesis testing to determine significance.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is Bias in statistical terms?

A

Is it centered in the right place? Refers to skewness in data.

Low bias indicates that estimates are close to the true value.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Define Reliability.

A

The repeatability and consistency of a measurement.

High reliability means that repeated measurements produce similar results.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What is Validity?

A

The relevance of a measurement or assessment.

It reflects how well a test measures what it is intended to measure.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What is Chance Error?

A

The random deviation in a sample due to natural fluctuations when drawing from a population.

It is an unavoidable error in sampling.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What is Variance?

A

A statistical measure of how much a set of values deviates from the mean.

It indicates the spread or dispersion of a data set.

18
Q

What is a Response Variable?

A

The outcome or variable being measured in a study, influenced or predicted by other variables.

It is often the dependent variable in an experiment.

19
Q

What is an Explanatory Variable?

A

The variable that explains, predicts, or influences changes in the response variable.

It is often considered the independent variable in an analysis.

20
Q

What is Randomization?

A

The process of assigning individuals or units in a study to different groups using a random method.

It ensures each unit has an equal chance of being placed in any group, reducing bias.

21
Q

What is Restricted Randomization?

A

Methods that impose certain constraints on the randomization process to ensure balance between treatment groups in an experiment.

It can help control for confounding variables.

22
Q

What does Blocking do in an experiment?

A

Converts unplanned, systematic variation into planned, systematic variation.

It helps to control for variables that could affect the outcome.

23
Q

What is a Blocking Variable?

A

A variable used to create blocks in an experiment to control for variability.

Examples include age, gender, or any other relevant characteristic.

24
Q

What does Replicate mean in an experimental context?

A

An independent run of an experimental condition to estimate variability.

Replication is crucial for validating experimental results.

25
What is an Experimental Unit?
The chunk of material that is assigned the treatment. ## Footnote It is the smallest division of experimental material.
26
What is an Observational Unit?
The chunk of material that is observed in a study. ## Footnote It may differ from the experimental unit depending on the study design.
27
What is a Factor in an experiment?
A variable that can cause changes in the output (response). ## Footnote Experimental factors are manipulated by the researcher.
28
What is a Treatment in experimental design?
A combination of factor levels whose effect is compared with other treatments. ## Footnote It represents how the experimental unit is manipulated.
29
What does Nominal data represent?
Response is a non-numerical category, never use ANOVA. ## Footnote Examples include categories like 'yes' or 'no'.
30
What is Ordinal data?
Responses can be ordered, but there is no meaningful notion of distance between categories. ## Footnote Example: Likert scales on professor evaluations.
31
What is Interval data?
Responses are numbers with a meaningful notion of distance between categories. ## Footnote Example: Temperature, where 0 does not represent an absence of temperature.
32
What is Ratio data?
Numbers with a meaningful notion of distance and relative size, where 0 means the absence of something. ## Footnote Example: Salary, where $8 vs. $16 indicates a ratio.
33
What is Causation?
The relationship between two variables where a change in one variable directly causes a change in another. ## Footnote It implies a direct influence rather than mere correlation.
34
What is Inference in statistics?
The process of drawing conclusions about a population based on data collected from a sample. ## Footnote It is a fundamental aspect of statistical analysis.
35
What is Interaction in experimental design?
The failure of one factor to produce the same effect on the response at different levels of another factor. ## Footnote It indicates that the effect of one factor depends on the level of another factor.
36
What is Selection Bias?
When the sample used in a study is not representative of the population due to non-random selection. ## Footnote It can lead to skewed results and invalid conclusions.
37
What does BF[1] refer to in experimental design?
Randomizes the entire group, no blocking or grouping, one factor. ## Footnote This is a basic randomization approach.
38
What does BF[2] refer to in experimental design?
Randomizes the entire group, no blocking or grouping, two factors. ## Footnote It allows for the examination of interactions between two factors.
39
What does CB[1] refer to in experimental design?
Groups into blocks, one factor, treatments are randomly assigned at the block level, restricted randomization once for every single group. ## Footnote This method controls for variability within blocks.
40
What does SP/RM[1;1] refer to in experimental design?
Groups into blocks, assigning treatments at two different levels. ## Footnote This approach allows for more complex interactions in experimental design.