when I reject the null hypothesis and when I accept the null hypothesis There are 2 steps to solve this one. Solution 100% (1 rating) Share Step 1 1. Rejecting the Null Hypothesis (H0): - When conducting hypothesis testing, you start with the nu...View the full answer...
The probability that you fail to reject the null hypothesis when in fact the alternative is true is called a Type ___ error. True or False: When a true null hypothesis is rejected, the researcher has made a Type I error. If we accept a null hypothesis when it is ...
When the null hypothesis is false, you cannot make Type II error. True False Type II Error: In the hypothesis testing, we have two types of error: type I error and type II error. The type II error is also known as the consumer risk,β. The type I error is also known...
A p-value of 0.08 being more than the benchmark of 0.05 indicates non-significance of the test. This means thatthe null hypothesis cannot be rejected. ... Accordingly, if your p-value is smaller than your α-error, you can reject the null hypothesis and accept the alternative hypothesis. ...
(detecting a male when it is female). Furthermore, as the applied psychometry has demonstrated (Chadha,2009), the false negative error (i.e., type I error rejecting the null hypothesis [H0] when it is true: detecting a female when there are male characteristics) and a false positive (i...
Use the formula to calculate the chi-square value. Find the critical chi-square value using a chi-square value table orstatistical software. Determine whether the chi-square value or the critical value is the larger of the two. Reject or accept the null hypothesis. ...
Null hypothesis accepted: Differences are not statistically significant The t-test is just one of many tests used for this purpose. Others may be more appropriate depending on the number of variables or the size of the sample. For example, statistici...
In most cases, we are looking to see if we can show that we can reject the null hypothesis and accept the alternative hypothesis, which is that the population means are not equal:HA: u1≠ u2To do this, we need to set a significance level (also called alpha) that allows us to either...
Specifically, it tests the null hypothesis:where µ = group mean and k = number of groups. If, however, the one-way ANOVA returns a statistically significant result, we accept the alternative hypothesis (HA), which is that there are at least two group means that are statistically ...
True or false? No error is committed when the null hypothesis is rejected when it is false. You do not accept the null hypothesis when you fail to reject it. True or false? If the null hypothesis is not rejected, what do we conclude about the null hypothesis?