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Flashcards in Midterm 1 Deck (47):
1

What are the four warnings in creating a histogram?

Choice of bin size has big affect
Changing axis range
Burying explanatory factors
How data is scaled

2

How are strip charts better than histograms?

Better for comparing multiple data series

3

What is the second step in sizing up data

Calculate Numerical descriptors
Mean
Median
Mode
Quantiles
Variance
Standard deviation
Min and max

4

What are boxplots?

Graphical form of the quantiles

5

What does the line inside a box in a boxplot represent?

Line indicates the median

6

What does the box hold in a boxplot?

Box holds 50% of points

7

What are the whiskers in a boxplot?

The whiskers hold remaining points

8

What is a null hypothesis

Conservative statement saying that there isn't an expected effect

9

What is a p-value

A measure of the strength of the evidence against a null hypothesis

10

How do we find the confidence level?

(1-p) x 100

11

What is sums of squares and how is it measured?

SSY is how we measure variability
Sum of each value minus grand mean squared

12

What is the relationship between SSY and n

SSY always increases with n

13

How to find variance

SSY/ n-1

14

what is the equation for standard variation

Square root of variance

15

What are the three variability arising in a data set?

Variability of the population (sigma)?
Variability by the sample (s)
Variability of the estimated mean

16

Why is standard error of the mean important

SEM can give us confidence intervals for our estimate of the population mean

17

How to find confidence intervals

Mean-tcrit (SD/ square root of sample size)

18

Relationship between estimate range and confidence level

A wider estimate range gives you a high confidence level

19

What is ANOVA

Analyze the difference among group means. Compare differences in values between treatments to the variation within a treatment group

20

What is the response variable

A continuous variable that is being influenced

21

What is a explanatory variable

Categorical or continuous variable that influences

22

In ANOVA, how do you find the total mean square

SSY/ df

23

What is linear regression

Can the value of he response variable(x) be predicted by the explanatory variable

24

Differences between ANOVA and regression?

ANOVA: discrete x values, values are names, values are unordered
Regression: continuously varying, values have number meaning, values are ordered

25

What is statistical elimination?

Including the second extra lavatory variable allowed us to eliminate its influence in the rest of our model

26

What are the four principles of experimental design?

Replication
Randomization
Blocking
Orthonogonality

27

What is replication

Multiple measures of the same thing
Appears in the # of error degrees of freedom(residuals)
Have at least 10 df for error

28

What is randomization

Treatments need to be applied to experimental units randomly
Use uniformly distributed random numbers

29

What cardinals sins does randomization avoid

Systemic design: similarity between plots that undermines replication

Unconscious bias in assigning treatment groups

Using haphazard bs random design

30

What is blocking?

Tool to minimize error variation

Distribute individual data points into different "blocks" yo minimize biases due to known common features of subsets of the points

Acts as another explanatory variable

31

What are the rules for block design

Blocks used to account for a factor that could influence response

Blocks should be used as internally homogeneous as possible

If possible, all treatments should be included in all blocks

32

What is Latin square design

2 way blocking. Blocking so that each treatment appears exactly once in each row and column:

33

What is orthogonality

The acknowledgement that one variable tell you nothing about the other variable

34

What is the benefit of orthogonal design

There is no statistical elimination between orthogonal explanatory variables

35

Which variables are easier for orthogonality

Easier for categorical variable than continuous variables

36

What is the first step in sizing up data?

Make a graph

37

In continuous explanatory variables what do the p-values in ANOVA table represent?

That each explanatory variable has no influence on the response variables

38

With continuous variables, what do the p-values represent in the coefficients table

That each specific coefficient value equals zero

39

In a continuous variable, what does the p-value mean overall?

Neither explanatory variables can be used to predict the response variable

40

In a categorical variable, what does the p-value mean in the ANOVA table?

That each explanatory variable has no influence in the response variable

41

In a categorical variable what does the p-value mean in the coefficients table mean?

Each specific coefficient value equals 0

42

In a categorical variable, what does the overall p-value mean in the coefficients table?

That neither of the variables can be used to predict the response variable

43

How does blocking affect residuals?

Blocking helps by reducing the size of the residuals. Increasing F but lowering P

44

What is an interaction

Two x-variables interact of the effect of one x-variable on y depends on the level of the other

45

Regarding interactions, what does non-parallel lines indicate

There is an interaction

46

Regarding interactions, what does two parallel line indicate?

There are no interactions

47

In which case are r-squared values high and low with and without interactions

Model without interactions have a low r- squared value while model with interactions have a higher-squared values