Following are commands in SPSS-17 version for starting ANCOVA (a) Analyze (b) Multivariate (c) Univariate (d) General linear model (e) Repeated measures Select the correct sequence of commands from the options given below :
(a), (d) and (c)
The question asks for the correct sequence of commands in SPSS version 17 (or similar recent versions) to initiate an Analysis of Covariance (ANCOVA). ANCOVA is a statistical technique that combines ANOVA (Analysis of Variance) with regression. It is used to compare means of a dependent variable across different groups while statistically controlling for the effects of one or more continuous variables, known as covariates.
In SPSS, statistical procedures are typically accessed through the 'Analyze' menu. ANCOVA falls under the category of General Linear Models because it analyzes the relationship between variables using linear equations, similar to ANOVA and regression.
When you want to perform a standard ANCOVA with a single dependent variable, you would select the 'Univariate' option within the 'General Linear Model' submenu. The term 'Univariate' indicates that there is one dependent variable being analyzed.
The standard path to access the ANCOVA dialog box in SPSS involves the following sequence:
Let's look at the options provided in the question and match them with the command sequence:
We are looking for the sequence that leads to a standard ANCOVA for a single dependent variable.
The correct sequence based on the step-by-step process is:
Analyze > General Linear Model > Univariate
Matching this with the options (a) through (e):
(a) Analyze > (d) General linear model > (c) Univariate
Therefore, the correct sequence of commands in SPSS-17 version for starting ANCOVA (with a single dependent variable) is (a), (d), and (c).
| Step | SPSS Menu Command | Option in Question |
|---|---|---|
| 1 | Analyze | (a) |
| 2 | General Linear Model | (d) |
| 3 | Univariate | (c) |
ANCOVA, or Analysis of Covariance, is a statistical method used to test for differences in means among two or more groups, while also controlling for the effect of a continuous variable (covariate) that might influence the dependent variable. By including a covariate, ANCOVA can increase the power of the test by reducing the error variance. It helps to account for initial differences between groups that existed before the intervention or group assignment.
Key elements in an ANCOVA:
ANCOVA assumes linearity between the dependent variable and the covariate, homogeneity of regression slopes (the relationship between the dependent variable and covariate is the same across all groups), and other assumptions similar to ANOVA (normality of residuals, homogeneity of variances).
Match List-I with List-II :
List-I | List-II | ||
(a) | The most commonly used method of computing correlation between two variables | (i) | Intra-class correlation |
(b) | An ANOVA technique used for estimating reliability of a measure | (ii) | Inter-class correlation |
(c) | A technique used for estimating reliability of multiple-trials tests | (iii) | Inter-tester reliability |
(d) | A form of reliability that pertains to the testers | (iv) | Coefficient alpha |
Select the correct option :
Given below are two statements
Statement I: Paired t-test is used to compare two related means (μ 1 and µ 2)
Statement II: The t-test is a method used for inferential statistics
In light of the above statements, choose the most appropriate answer from the options given below
Match the items of List I with the items of List II and choose the correct answer from the code given below.
List – I | List – II | ||
a | X̅ chart | i | Number of defects |
b | P chart | ii | Variations between samples |
c | C chart | iii | Variations within samples |
d | R chart | iv | Proportion of defectives Code |
If mean, median, mode and standard deviation are known for a given data set, the Pearson's first skewness coefficient is equal to
Following commands are used in SPSS-17 version for factor analysis :
(a) Analyse
(b) Factor
(c) Data reduction
Select the correct sequence from the following :