StatPowers
Data Entry
?
✖
Enter paired data separated by comma, semicolon, space or tab.
Each pair should be placed on a new line.
Vars
Units
Calculate Now
Clear All
Share Data
Summary Statistics
Differences
Calculate Differences as:
X − Y
Y − X
Normality
QQ Plot:
choose a variable
X
Y
residuals
differences
95% Bands
Worm Plot | GOF Bins:
Your browser doesn't support canvas. Please update your browser.
Charts
Histogram (Differences)
?
✖
If your data is discrete (integers) the histogram will probably look better if you select "Discrete Bars" - however if the range of your data is too large you will end up with spikes and gaps. In this case it would be better to not use Discrete Bars. You can use one of the rules of thumb (Square root n, Sturges', etc.) to automatically choose the number of bins, or you can specify from 4 to 20 bins.
Discrete Bars (only for integer data)
Overlay normal curve
Number of bins:
Square-Root of n
Sturges' formula
Rice Rule
Doane's formula
Scott's normal reference rule
Freedman-Diachonis' choice
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Your browser doesn't support canvas. Please update your browser.
Scatter Plot
Show Trend Line
Show Confidence Interval Band
Show Prediction Interval Band
Your browser doesn't support canvas. Please update your browser.
Hex Plot
Resolution:
Marginal Distributions
Your browser doesn't support canvas. Please update your browser.
Bag Plot
Your browser doesn't support canvas. Please update your browser.
Kernel Density Plot
Kernel Method:
Gaussian
Epanechnikov
Resolution:
Low
Medium
High
Very High
Contours:
none
1
2
3
4
5
6
7
8
9
Gray for Zero
Marginal Densities
Your browser doesn't support canvas. Please update your browser.
Residual Plot
Your browser doesn't support canvas. Please update your browser.
Confidence Intervals
Confidence Level
Mean of Differences Estimation
Correlation Estimation
Hypothesis Testing
Significance Level (α)
T Test for Mean Difference
H
0
:
μ
X
− μ
Y
=μ
D
=
H
1
:
μ
X
− μ
Y
=μ
D
<
>
≠
0
Test for Correlation
H
0
: ρ
=
H
1
: ρ
<
>
≠
0
Test for Median
?
✖
(notes to come)
H
0
: θ
d
=
H
1
: θ
d
<
>
≠
0
Simple Linear Regression
Response Variable:
Y
X
Prediction:
X
=