Statistical Analysis in Socioeconomic Research: Methods and Applications
Test: Objective
Drawing Conclusions and Ascertaining the Importance of Economic Management
Draw conclusions and ascertain the importance of economic management, depending on whether individuals are employed (yes/no).
Conclusions (indicating value means)
- Importance of “1”: The second chart shows a degree of proof for Levene’s test for equal variances of 0.654 > 0.05. Therefore, Ho is accepted. So, the means (bilateral) for the T-test equal smear result medium (Ho: µ1 = µ2) is 0.436 > 0.05. Then, Ho is accepted. There is equality of means (means are not significant).
- Importance of “2”: The same.
Variable Types Required for the Above Analysis
- T-test using two types of variables:
- Dependent Variable (continuous): Importance of economic management and import of what is seen.
- Independent Variable: To get paid (yes/no). The type is categorical.
Types of Fishing Village Sesimb and Variables Tested
- Independent T-test:
- Categorical Variable: Commercial
- Continuous Variable: Salary level
- T-test for related samples:
- Continuous Variable: Level of wages
Independent Sample T-Test
Ho: The mean wages (original and current) are equal (µ = µh).
H1: Different.
Related Sample T-Test
Equality of means between the initial and final salary. How are Ho and H1? How do you interpret the data from each T-test?
- Ho: There is no difference in means.
- H1: There is a difference.
Comparisons
Say: The p-value of Levene’s test is < 0.05, so Ho is rejected. Do not assume equal variances (the same for stockings).
Conclusions
The average is higher than that.
Sociodemographic Composition
Using statistical techniques (contingency table: categorical variable/continuous variable T-tests).
Factor Analysis (AF):
Reduction Techniques
Data aimed to identify a few factors among a broader set of variables, allowing us to interpret reality more easily.
Design
With a total of 781 observations, the investigation is carried out through descriptive methods, in particular, the staff survey, using a Likert scale of 1-5, with 1 being very low.
Fitness
- Matrix correlation with near 0.
- KMO index > 0.5.
- Barlett < 0.05.
- MAM > 0.7.
Factor Extraction, Eigenvalues, Commonly Accepted Variance
We note in Table 3 that the correlation matrix is constructed of factor loadings.
- Variance: The component 1 explains the penultimate column’s percentage of the amount of variation, and so on.
- Communality: Values < 0.4 are significant problems because they are not associated with any factor in the matrix. Delete and redo the analysis. Here, we cannot do it.
- Eigenvalue: The number of factors is determined by making those older than 1 explain the percentage of the last (in the last column).
- Rotation of Factors: Transforming the matrix into a simpler factorial does not affect the goodness of fit and does not change this (communality). It only redistributes.
Two types of rotation (oblique and orthogonal -Varimax- that we interpret) augment the factors. They are then grouped into functions based on having coefficients > 0.5, and names are given to groups.
Utility
Characterized by greater simplicity and interpretability, the construction of dimensional spaces allows for the psychology of the object of study, and allows for an analysis (competence, similarity of perceptions, and identifying market niches).