DATA ANALYSIS WITH SPSS

What is the purpose of Descriptive Statistics in data analysis?

• Descriptive Statistics helps in making causal inferences in data analysis.

• The purpose of Descriptive Statistics in data analysis is to summarize and describe the main features of a dataset.

• Descriptive Statistics is used to predict future trends in data analysis.

• Descriptive Statistics focuses on identifying outliers in data analysis.

Explain the concept of Hypothesis Testing and its significance in research.

• Hypothesis Testing is not necessary in research

• Hypothesis Testing is only applicable in qualitative studies

• Hypothesis Testing is a statistical method used to make inferences about a population parameter based on sample data.

• Hypothesis Testing is a method used to prove causation in research

How is Correlation Analysis used to measure the relationship between variables?

• Correlation Analysis is only applicable to categorical variables

• Correlation Analysis uses regression analysis to determine the relationship

• Correlation Analysis measures the average of the variables

• Correlation Analysis calculates the correlation coefficient to measure the relationship between variables.

What is Regression Analysis and how is it different from Correlation Analysis?

• Regression Analysis measures the strength and direction of a relationship between variables.

• Regression Analysis and Correlation Analysis are the same.

• Regression Analysis predicts values of dependent variables, while Correlation Analysis measures the strength and direction of a relationship between variables.

• Correlation Analysis predicts values of dependent variables.

Describe the role of ANOVA in statistical analysis.

• ANOVA is used to compare variances of two groups in statistical analysis.

• ANOVA is used to determine correlations between variables in statistical analysis.

• ANOVA is used to compare means of three or more groups in statistical analysis.

• ANOVA is used to calculate medians of three or more groups in statistical analysis.

What is Factor Analysis and when is it used in data analysis?

• Factor Analysis is used in data analysis to predict future trends accurately.

• Factor Analysis is used in data analysis to reduce data dimensions and identify underlying latent variables.

• Factor Analysis is used to increase data dimensions and identify visible variables.

• Factor Analysis is used to analyze categorical data and identify outliers.

How is Cluster Analysis used to group data points based on similarities?

• By randomly assigning data points to clusters without considering similarities

• By sorting data points alphabetically and assigning them to clusters accordingly

• By measuring the distance between data points and assigning them to clusters where the points are closer to each other than to points in other clusters.

• By ignoring the distance between data points and assigning them to clusters based on their values

What are the different types of clustering methods used in Cluster Analysis?

• Spectral clustering

• Normal Clustering

• K-means clustering, Hierarchical clustering

• Linear regression

What is the significance of Multivariate Analysis of Variance (MANOVA) in statistical analysis?

• MANOVA is used to compare variances of two groups in statistical analysis.

• MANOVA is primarily used in medical research.

• MANOVA is used to compare means of three or more groups in statistical analysis.

• MANOVA is used to analyze univariate data only.

Including too many predictor variables in regression models can lead to

• Underfitting

• Overfitting

• Balanced fitting

• Perfect model fit