Pair-Sample t-test
1. ttestpair irng:=(Col(a), Col(b));
2. ttestpair irng:=(Col(a), Col(b)) mdiff:=0.5;
3. ttestpair irng:=(Col(a), Col(b)) tail:=2;
4. ttestpair irng:=(Col(a), Col(b)) prob:=myprob;
Please refer to the page for additional option switches when accessing the x-function from script
Display Name |
Variable Name |
I/O and Type |
Default Value |
Description |
---|---|---|---|---|
Input | irng |
Input Range |
|
This variable specifies the input data ranges on which to perform a pair sample t-test. It should contain two columns with the same size. |
Hypothetical means difference | mdiff |
Input double |
|
This variable specifies the hypothetical difference between the paired sample means |
Tail | tail |
Input int |
|
This variable indicates whether an upper, lower or 2 tailed test is required. (Suppose m1 and m2 are sample means and m is the mean difference.) Option list
|
Significance level | alpha |
Input double |
|
This variable specifies alpha value, or the significance level value. With this value, the associated confidence interval will be computed. It should be larger than 0 and less than 1. |
T-Statistic | stat |
Output double |
|
Value of the paired-sample t-test statistic |
Degrees of freedom | df |
Output double |
|
Degrees of freedom for the paired-sample t-test. |
P-value | prob |
Output double |
|
Associated p-value of the test. Users can compare it with their desirable significance level (commonly 0.05). If the p-value is greater than or equal to that value, the null hypothesis is rejected. |
Lower confidence limit | lcl |
Output double |
|
The lower confidence limit for the hypothetical mean of the sample data. The confidence level is set as 100* (1-alpha) %. |
Upper confidence limit | ucl |
Output double |
|
The upper confidence limit for the hypothetical mean of the sample data. The confidence level is set as 100* (1-alpha) %. |
The Pair-Sample t-Test analysis determines whether the means of two same-sized and dependent samples from a normal distribution are equal or not, and calculates the confidence interval for the difference between the means. The pair-sample t-test also enables you to test whether or not the means of two samples differ by a specified amount. The term paired means that there is a dependence or correspondence between observations from each sample. For example, a paired t-test would be used when a laboratory process is changed, and equal numbers of data points are taken before and after the change in process. For unequal numbers of data points and independent data sets, use the 2-sample t-test, known as ttest2 in Origin.
To estimate the difference between two population means, the sample mean difference with confidence interval is also computed for each confidence levels.
Please read the help of PairSampletTest for detail algorithms
Snedecor, George W. and Cochran, William G. (1989), Statistical Methods, Eighth Edition, Iowa State University Press.