5.5 Warm Up 11.12.24 [STATS]
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Mathematics
•
9th - 12th Grade
•
Hard
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15 questions
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1.
FLASHCARD QUESTION
Front
What is the correlation coefficient and what does it indicate about the relationship between two variables?
Back
The correlation coefficient is a statistical measure that describes the strength and direction of a linear relationship between two quantitative variables. It ranges from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation.
2.
FLASHCARD QUESTION
Front
Define a block in the context of experimental design.
Back
A block is a group of experimental units that are similar in some way and are treated as one experimental unit. Blocking is used to reduce variability and improve the accuracy of the experiment.
3.
FLASHCARD QUESTION
Front
What does the standard deviation measure in a data set?
Back
The standard deviation measures the typical or common distance that observations are away from the mean of the data set. It quantifies the amount of variation or dispersion in a set of values.
4.
FLASHCARD QUESTION
Front
What is a sample space in probability?
Back
A sample space is the set of all possible outcomes of a chance process or experiment. It includes every possible result that can occur.
5.
FLASHCARD QUESTION
Front
Explain what bias means in the context of a study's design.
Back
Bias refers to a systematic error in the design of a study that leads to an overestimation or underestimation of the true value. It can affect the validity of the study's conclusions.
6.
FLASHCARD QUESTION
Front
What is the difference between correlation and causation?
Back
Correlation indicates a relationship between two variables, but it does not imply that one variable causes the other. Causation means that changes in one variable directly result in changes in another.
7.
FLASHCARD QUESTION
Front
What is the purpose of using blocks in experimental design?
Back
The purpose of using blocks in experimental design is to control for variability among experimental units, allowing for a more accurate comparison of treatments by reducing confounding factors.
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