1. central tendency: a statistical measure to determine a single score that defines
the center of a distribution; the most typical or most representative value
2. Mean: The average of a set of numbers
3. Median: the middle score in a distribution; half the scores are above it and half
are below it
4. Mode: the most frequently occurring score(s) in a distribution;
5. Issues with mean: Can be influenced by outliers
6. Issues with Mode: Some data sets may not have one. Can be influenced by
outliers
7. Range: measure of variability, spread, dispersion
Max-Min
8. Limitations of Range: only uses Minimum and Maximum values. Considers
only 2 values
9. Two reasons to use a Z-Score: -Tells you the exact location of the raw score
within distribution
-Allows us to compare with other distributions due to standardization
10. Properties of Z-Scores: -The shape of the distribution of the z-score will be the
same as the shape of the distribution of the raw scores
-Mean on z-scores = 0
-Standard Deviation = 1
11. Conditions needed for a valid large sample Confidence Interval: -A random
sample is selected from the target population. -The sample size is greater than
or equal to 30
-Due to the CLT, this condition guarantees that the sampling distribution of X-bar is
approx. normal
12. Point Estimator: a sample statistic used to estimate the corresponding
population parameter
13. Interval Estimator: a formula that tells us how to use the sample data to
calculate an interval that estimates the target parameter
14. How to narrow a confidence interval: -increase sample size
-lower confidence level
15. Conditions for a valid small sample confidence interval: -Random from
target population
-Comes from approx. normal population
-Theorem 5.1 allows us to claim if the population is approx. normal that the sampling
distribution of X-bar is approx. normal
16. If nothing is known about variable x in a small sample: sampling distribution
is unknown
the center of a distribution; the most typical or most representative value
2. Mean: The average of a set of numbers
3. Median: the middle score in a distribution; half the scores are above it and half
are below it
4. Mode: the most frequently occurring score(s) in a distribution;
5. Issues with mean: Can be influenced by outliers
6. Issues with Mode: Some data sets may not have one. Can be influenced by
outliers
7. Range: measure of variability, spread, dispersion
Max-Min
8. Limitations of Range: only uses Minimum and Maximum values. Considers
only 2 values
9. Two reasons to use a Z-Score: -Tells you the exact location of the raw score
within distribution
-Allows us to compare with other distributions due to standardization
10. Properties of Z-Scores: -The shape of the distribution of the z-score will be the
same as the shape of the distribution of the raw scores
-Mean on z-scores = 0
-Standard Deviation = 1
11. Conditions needed for a valid large sample Confidence Interval: -A random
sample is selected from the target population. -The sample size is greater than
or equal to 30
-Due to the CLT, this condition guarantees that the sampling distribution of X-bar is
approx. normal
12. Point Estimator: a sample statistic used to estimate the corresponding
population parameter
13. Interval Estimator: a formula that tells us how to use the sample data to
calculate an interval that estimates the target parameter
14. How to narrow a confidence interval: -increase sample size
-lower confidence level
15. Conditions for a valid small sample confidence interval: -Random from
target population
-Comes from approx. normal population
-Theorem 5.1 allows us to claim if the population is approx. normal that the sampling
distribution of X-bar is approx. normal
16. If nothing is known about variable x in a small sample: sampling distribution
is unknown
