Statement I When a null hypothesis is true but as per the hypothesis testing, it is rejected; it is known as Type II error in hypothesis testing.<br>Statement II For testing the significance of the differences among the performance of more than two sample groups when the data are non-parametric, Kruskal-Wallis (H) test is appropriate.

Statement I When a null hypothesis is true but as per the hypothesis testing, it is rejected; it is known as Type II error in hypothesis testing.
Statement II For testing the significance of the differences among the performance of more than two sample groups when the data are non-parametric, Kruskal-Wallis (H) test is appropriate. Correct Answer Statement I is incorrect, while Statement II is correct

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Related MCQ's

A researcher wants to test the significance of the differences of the average performance of more than two sample groups drawn from a normally distributed population, which one of the following hypothesis testing tests is appropriate?

Which of the following statements are true?
Statement I Big data refers to no precise quantity, but generally refers to data in the range of Petabytes and Exabyte, i.e. billions to trillions of records, all from various sources. Big data is generated much faster. than traditional data in much larger quantities.
Statement II Big data interests industries because they are able to learn more patterns and curious variances than smaller data sets, with the capability to provide valuable insights into consumer behaviour, weather systems, financial market activity, or other phenomena.
Statement III Various departments and product lines use various applications within most organisations and store data in separate datasets. These separate databases may contain similar data, but data from one data base to another is not always consistent. This is called data silo.

Statement I A hypothesis test for comparing the variances of two independent populations with the help of variances of two small samples is known as chi-square test.
Statement II To test the hypothesis that the population standard deviation has a specific value on the basis of the values of sample standard deviation of small sized sample, F-test isrelevant.

Consider the following statement and identify the wrong statements.
Statement I: Accepting null hypothesis, when it is false, is called a level of significance.
Statement II: $$1 - \alpha $$  is called power of a test.
Statement III: Critical value of $$Z$$ - static for two-tailed test at 5% level of significance is 1.96.

A researcher conduct a hypothesis test and observes values from sample mean and sample standard deviation when n = 25, that do not lead to rejection of null hypothesis. He calculates the p value as 0.0667. What will happen to the p value if he observes the same sample mean and standard deviation for a sample > 25?

In a medical test, where the null hypothesis is 'the patient does not have the disease' and the alternative hypothesis is 'the patient has the disease'. Suppose a patient has a disease and needs treatment. In the hypothesis testing process, which of the following error is more serious than the others.

In a test of differences between proportions, two samples are taken. In the first sample, a sample size of 100 shows 25 successes. In the second sample, a sample size of 80 shows 25 successes. What would be the value of B in this case?

In a two tailed test when a Null Hypothesis is rejected for a True Alternative Hypothesis then it has ____________

Point out the error (if any) in the following C code?
#include <stdlib.h>#include <stdio.h>int main(void){ int* p = NULL; struct S *s = NULL; void(*f)(int, double) = NULL; char *ptr = malloc(15); if (ptr == NULL) printf("Out of memory"); free(ptr);}

What is the probability of mistakenly failing to reject a false null hypothesis when a hypothesis test is being conducted at the 5% significance level (? = 0.05)?

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