![2 sample t test minitab 2 sample t test minitab](https://i.ytimg.com/vi/IHUWCCJufMs/maxresdefault.jpg)
Spreadsheets such as EXCEL contain a number of statistical functions, and these can be very helpful. The recent advent of spreadsheets and statistical/graphical software packages has transformed elementary statistical analysis from a rather mathematical subject, backed up by dense statistical tables, into a readily accessible technique. Analysis is the step between obtaining data and applying it to solve practical problems. Data analysis includes (i) organising measurements into a meaningful order or into groups, (ii) reducing the data into manageable quantities, (iii) forming succinct descriptions of the main features of the data, and (iv) elucidating any anomalies for subsequent examination. Measurements are of little use until they are 'analysed'. (Roy Thompson, Geology & Geophysics Department) Practical statistical analyses using MINITAB For more information, go to Power and Sample Size for 2-Sample t.Practical statistical analyses using Minitab You should make sure that your test has enough power to detect a difference that is practically significant. You do not have enough evidence to conclude that the difference between the population means is statistically significant. P-value > α: The difference between the means is not statistically significant (Fail to reject H 0) If the p-value is greater than the significance level, the decision is to fail to reject the null hypothesis. For more information, go to Statistical and practical significance.
![2 sample t test minitab 2 sample t test minitab](https://www.leansigmacorporation.com/wp/wp-content/uploads/2014/10/how-to-run-a-2-sample-t-test-in-minitab-05-300x208.png)
Use your specialized knowledge to determine whether the difference is practically significant. If you did not specify a hypothesized difference, Minitab tests whether there is no difference between the means ( Hypothesized difference = 0). You can conclude that the difference between the population means does not equal the hypothesized difference. P-value ≤ α: The difference between the means is statistically significantly (Reject H 0) If the p-value is less than or equal to the significance level, the decision is to reject the null hypothesis. A significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. Usually, a significance level (denoted as α or alpha) of 0.05 works well. To determine whether the difference between the population means is statistically significant, compare the p-value to the significance level. For more information, go to Ways to get a more precise confidence interval. If the interval is too wide to be useful, consider increasing your sample size. Use your specialized knowledge to determine whether the confidence interval includes values that have practical significance for your situation. The confidence interval helps you assess the practical significance of your results. For example, a 95% confidence level indicates that if you take 100 random samples from the population, you could expect approximately 95 of the samples to produce intervals that contain the population difference. The confidence interval provides a range of likely values for the difference between two population means. To better estimate the population difference, use the confidence interval for the difference. Because the difference is based on sample data and not on the entire population, it is unlikely that the sample difference equals the population difference.
![2 sample t test minitab 2 sample t test minitab](https://i.ytimg.com/vi/tRtttUBzkEk/maxresdefault.jpg)
The difference is an estimate of the difference in the population means. First, consider the difference in the sample means and then examine the confidence interval.