The analysis of variance technique was developed by:
RA Fisher
The question asks about the statistician who developed the Analysis of Variance technique, widely known as ANOVA. ANOVA is a powerful statistical method used to test for differences among two or more group means in a sample, considering variation within and between groups.
Let's look at the options provided:
The Analysis of Variance (ANOVA) technique is a fundamental concept in statistics and was developed by a specific statistician whose work significantly impacted experimental design and data analysis.
The statistician credited with developing ANOVA is Sir Ronald Aylmer Fisher, commonly known as R.A. Fisher. He introduced this technique in the 1920s while working at the Rothamsted Experimental Station in England. ANOVA was initially developed for analyzing data from agricultural experiments, but its application quickly expanded to various fields, including psychology, medicine, and social sciences.
Let's consider why the other options are not the correct answer for the development of ANOVA:
Based on the historical development of statistical methods, R.A. Fisher is the correct answer for the developer of the Analysis of Variance technique.
| Statistician | Known For (Examples) | Developed ANOVA? |
|---|---|---|
| RA Fisher | Analysis of Variance (ANOVA), Experimental Design, Maximum Likelihood, p-value concept | Yes |
| Karl Pearson | Pearson correlation, Chi-squared test, Founder of Biometrika | No |
| PC Mahalanobis | Mahalanobis distance, Sample Surveys, Indian Statistical Institute | No |
| Irving Fisher | Economics (Monetary Theory, Index Numbers) | No |
| Concept | Developer | Purpose |
|---|---|---|
| Analysis of Variance (ANOVA) | RA Fisher | Comparing means of two or more groups |
| Pearson Correlation | Karl Pearson | Measuring linear association between two variables |
| Chi-squared test | Karl Pearson | Testing association between categorical variables |
| Mahalanobis Distance | PC Mahalanobis | Measuring distance between a point and a distribution |
ANOVA is based on partitioning the total variability in a dataset into different sources. For example, in a simple one-way ANOVA, the total variation is split into variation between the groups being compared and variation within the groups (often called error). By comparing the ratio of the variance between groups to the variance within groups (using an F-test), we can determine if there is a statistically significant difference among the group means.
The null hypothesis in ANOVA typically states that the means of all groups are equal, while the alternative hypothesis states that at least one group mean is different from the others.
ANOVA is a foundational technique in statistics for analyzing data from experiments and observational studies where multiple groups are being compared.
Which of the following is NOT true for seasonal variation?
Index numbers are a type of:
If the mean, mode and quartile deviation of a distribution is 2, 7 and 3, respectively, then Karl Pearson's coefficient of skewness is given by:
Suppose that a sample of 100 independent draws from a normal distribution having unknown mean μ and known variance σ2 = 1 is observed. If the sample mean is 5, then the 95% confidence interval for μ is:
Which of the following is a merit of data tabulation?
In seasonal variations, the duration of time is not more than:
Consider the following ANOVA table.
| Source of variation | Degrees of freedom | The sum of Squares (SS) | Mean SS | F Ratio |
| Treatments | a | b | c | 5 |
| Error | 12 | d | 20 | |
| Total | 15 | 540 |
If the 25th, 50th and 75th percentile of a frequency distribution are equal to 2, 3 and 4, respectively, then the distribution is:
If for a data set, third quartile and median are equal, then Bowley’s coefficient of skewness is:
The component containing the overall upward or downward pattern of the data in an annual time series is:
Match the following:
| (a) Marginalist Revolution | (i) Samuelson |
| (b) Multiplier-Accelerator model | (ii) J. R. Hicks |
| (c) IS-LM curves | (iii) Jevous |
| (d) Real Business Cycle | (iv) Robert J. Borro |
Choose the correct option from those given below:
Which one of the following responses is true as a solution to simultaneous equation bias?
A. OLS method
B. Principle Component Method
C. Two - stage Least Square Method (2 SLS method)
D. Full Information Maximum Likelihood method (FIML)
Choose the correct option.
Time series under the condition (E xt ) = μ and cov(x t, x t + k ) = Y(K) is said to be
Given the sample size 400 with the sample mean 99, the population mean 100 and computed value of z statistic at 2.5, the value of population standard deviation will be
Which one of the following price index numbers satisfies the factor reversal test?