Parametric test, unlike the nonparametric tests, make certain assumption about :
The underlying distribution
Parametric tests (t-test, z-test, ANOVA) assume that the data come from a population with a specified distribution, usually normal, and use parameters such as the mean and standard deviation.
Nonparametric (distribution-free) tests such as chi-square, Mann-Whitney and Wilcoxon do not assume any particular distribution. Population size, sample size and sampling error are not the assumption that separates the two families.
Hence, the answer is The underlying distribution.
If a frequency distribution has some extreme scores, then appropriate measure of variability will be .........
Identify the correct sequence of the following activities associated with research data :
(i) Data collection
(ii) Construction of frequency tables
(iii) Cleaning of data
(iv) Presentation of data in charts.
Codes :
Which of the following is a correct about assumption of homogeneity of variance in t-test ?
In a standardized regression analysis, the value of intercept is :
The PCA shall :
What is the percentage of variance first unrotated PCA shall explain ?
Which of the following is correct about KMO value ?
How many factors can be retained for rotation using Guttman and Scree criteria ?
The varimax rotation shall result in :
Bartlett’s Test of Sphericity results indicate that correlation matrix of :
Given below are two statements:
Statement I: In two tail test, 2.5% of the area of the normal curve falls on the right of 1.96 standard deviations above the mean and 2.5% to the left of 1.96 standard deviations below the mean.
Statement II: In one tail test, for testing the difference between large sample means, a z score of 1.64 is taken as Yardstick at the 5% level of significance.
In light of the above statements, choose the most appropriate answer from the options given below:
In a traditional extract–transform–load (ETL) workflow, data scrubbing performed during the transformation stage is:
| Temperature (°C) | Number of stations |
|---|---|
| 0–10 | 1 |
| 10–20 | 2 |
| 20–30 | 3 |
| 30–40 | 4 |
| 40–50 | 5 |
| 50–60 | 4 |
| 60–70 | 3 |
| 70–80 | 2 |
| 80–90 | 1 |
Using the standard grouped-data interpolation formula with position 3N/4, estimate the third quartile Q₃ of the temperature distribution.
| Temperature (°C) | Number of stations |
|---|---|
| 0–10 | 1 |
| 10–20 | 2 |
| 20–30 | 3 |
| 30–40 | 4 |
| 40–50 | 5 |
| 50–60 | 4 |
| 60–70 | 3 |
| 70–80 | 2 |
| 80–90 | 1 |
Using class midpoints, what is the estimated arithmetic mean temperature?
| Temperature (°C) | Number of stations |
|---|---|
| 0–10 | 1 |
| 10–20 | 2 |
| 20–30 | 3 |
| 30–40 | 4 |
| 40–50 | 5 |
| 50–60 | 4 |
| 60–70 | 3 |
| 70–80 | 2 |
| 80–90 | 1 |
Using the standard grouped-data interpolation formula, what is the estimated median temperature?