Exploring 1 variable data
2 Variable Data
MISC
Probabilities
Significance Testing
100

CSOCS - Context, Shape, Outliers, Center, Spread

How do you describe a distribution?

100

Describe a correlation 

The linear association between x-context and y-context is weak/moderate/strong (strength) and positive/negative (direction).

100

We are % confident that the interval from A to B captures the true parameter context.

Interpret the Confidence Interval

100
Interpret the probability

After many many context, the proportion of times that context A will occur is about P(A)

100

The Ha context is true, but we don’t find convincing evidence for Ha context.

What is a Type 2 Error?

200

Interpret the Z-Score.


Specific value with context is z-score standard deviations above/below the mean.

200

Interpret the Residual

The actual y-context was residual above/below the predicted value when x-context = #.

200

Interpret the Slope

The predicted y-context increases/decreases by slope for each additional x-context.

200

If the random process of context is repeated for a very large number of times, the average number of x-context we can expect is expected value.

Interpret the Expected Value.

200

Conclusion for a Significance Test

Because p-value p-value < / > significance level we reject / fail to reject H0. We do / do not have convincing evidence for Ha in context.

300

Describe a Distribution

CSOCS - Context, shape, outliers, center, spread

300

Describe the relationship

DUFS - Direction, Unusual Points, Form, Strength

300

Interpret the Confidence Level

If we take many, many samples of the same size and calculate a confidence interval for each, about confidence level % of them will capture the true parameter in context

300

Interpret the conditional probability

Given context B, there is a P(A|B) probability of context A

300

Interpret a P-value

Assuming Ho in context , there is a p-value probability of getting the observed result or less/greater/more extreme, purely by chance.

400

Interpret a Percentile.


percentile % of context are less than or equal to value.

400

The actual SAT score is typically about 14.3 points away from the value predicted by the LSRL.

Standard Deviation of Residuals

400

The sample proportion of success context typically varies by 𝜎p from the true proportion of 𝑝

Standard Deviation of Sample Proportions

400

Interpret the Binomial Standard Deviation

The number of success context out of n typically varies by 𝜎x from the mean of πœ‡x 

400

Type 1 Error

The Ho context is true, but we find convincing evidence for Ha context.

500

Interpret the Standard Deviation.

The context typically varies by SD from the mean of mean.

500

Interpret the Coefficient of Determination

About π‘Ÿ2% of the variation in y-context can be explained by the linear relationship with x-context.

500

The sample mean amount of x-context typically varies by 𝜎from the true mean of πœ‡x.

Standard Deviation of Sample Means

500

Interpret the Binomial Mean

After many, many trials the average # of success context out of n is πœ‡x.

500

Standard Error of the Slope (SEb)

The slope of the sample LSRL for x-context and y-context typically varies from the slope of the population LSRL by about SEb context.