Match the LIST-I with LIST-II
LIST-I
Test SituationLIST-II
Parametric TestA. One Mean I. p-value $0.474$ B. Two Independent mean II. p-value $0.703$ C. Two dependent mean III. p-value $0.550$ D. Correlation (Pearson's) IV. p-value $0.564$
Choose the correct answer from the options given below:
Solution: Parametric Test Matching
This question requires matching specific statistical tests (LIST-I) with their corresponding p-values (LIST-II). The focus is on parametric tests. The provided p-values are all relatively high, indicating non-rejection of the null hypothesis in each scenario at conventional significance levels.
Matching Parametric Tests with P-values
Based on the correct answer provided, the matching is as follows:
- A. One Mean is matched with I. p-value $0.474$. This typically corresponds to a one-sample t-test or z-test, where the p-value suggests no significant difference from the hypothesized population mean.
- B. Two Independent Means is matched with IV. p-value $0.564$. This relates to an independent samples t-test, indicating no statistically significant difference between the means of two unrelated groups.
- C. Two Dependent Means is matched with III. p-value $0.550$. This aligns with a paired samples t-test, suggesting no significant difference between the means of two related measurements (e.g., before and after).
- D. Correlation (Pearson's) is matched with II. p-value $0.703$. This signifies a test for the linear association between two variables. The high p-value indicates a lack of significant linear correlation.
Understanding P-values in Hypothesis Testing
In hypothesis testing, the p-value quantifies the probability of observing test results at least as extreme as the results actually observed, assuming the null hypothesis is true. A high p-value (typically > $0.05$) suggests that the observed data are not sufficiently unusual to reject the null hypothesis.
The matching reflects plausible scenarios where parametric tests were conducted, and the results did not meet the threshold for statistical significance.
Important Questions from Hypothesis testing - Teaching
- Type II error occurs when :
- The null hypothesis in nonparametric test often _______.
1. Includes specification of a population's parameters
2. Is used to evaluate some general population aspect
3. Is very similar to that used in regression analysis
4. Simultaneously tests more than two population parameters - The _______ test determines whether there is a significant difference between the observed and hypothesized distribution for a sample.
1. Independence
2. Coefficient of determination
3. Correlation analysis
4. Goodness-of-fit - Match the LIST-I with LIST-II
LIST-I LIST-II A. One-Tailed Test I. Null hypothesis is rejected if the sample value is significantly higher or lower than the hypothesized value of the population parameter B. Paired difference Test II. A hypothesis test of the difference between the sample means of two independent samples C. Two-Tailed Test III. A sample value significantly above the hypothesized population value will lead to rejection of the null hypothesis D. Upper-Tailed Test IV. Concerned only with whether the observed value deviates from the hypothesized value in one direction
Choose the correct answer from the options given below: - The null hypothesis that all slope coefficients are simultaneously equal to zero is tested in logit model by:
