Explain what are multivariate analysis and the objectives of multivariate analysis. Also differentiate between principal component and factor analysis with examples

Q: Explain the term Continuous Quantitative Data?

A: Continuous data is Quantitative data. Continuous Quantitative data is which can be measured or…

Q: What are the assumption and observation of regression analysis?

A: Regression analysis: Regression is the mathematical method that determines the mean association…

Q: What is factor analysis? How does it differ from principal components analysis? Describe a typical…

A: Factor analysis: In statistics, factor analysis is basically used to explain variability in the…

Q: What are the assumptions of the Regression analysis?

A:

Q: Why Bayesian modelling and  analysis over others?

A: Bayesian modelling finds the best out of the uncertainty. Every state in the models is assigned a…

Q: Identify six problems that can arise in data collection for a regression analysis.

A:

Q: Explain how, when and why we use Qualitative ( Categorical)  type Independent variables in Multiple…

A: Categorical type independent variable in Multiple regression analysis

Q: How can we explain sentiment analysis applications with Bayes Theorem?

A:

Q: Why Estimated coefficients are used?

A: An estimated coefficient is a multiplicative factor in some terms of a polynomial, a series, or any…

Q: how do you construct scatter plots for bivariate data? an example would help.

A: Bivariate data is data with two variables. A Scatter plot is plotted to identify the relationship…

Q: what are some additional challenges we face in conducting multiple regression analysis?

A: Challenges that we face in conducting multiple regression analysis is :

Q: Explain how multicollinearity can adversely affect the model building process in regression…

A: Multicollinearity:Multicollinearity is the presence of high correlation among the predictor…

Q: What is the difference between correlation analysis and regression analysis?

A:

Q: analyze the multiple regression?

A: Multiple regression is an expansion of simple linear regression. It is used to be predicted the…

Q: Two-dimension coding of quantitative data in charts is not the best practice? True or false?

A: Quantitative coding is the process of categorizing the collected non-numerical  information…

Q: Discuss the differences between quantitative and qualitative data, as well as the advantages and…

A: In statistics, according to measurement, data can be categorized in two types, such as quantitative…

Q: What is the least squares method and how is it used to find the estimated regression equation? What…

A: The least squares method is a form of mathematical regression analysis used to determine the line of…

Q: Show the difference between the "complete model" and "reduced model of regression analysis?

A:

Q: Give five examples where the use of regression analysis can be beneficially be made.

A: Answer: For the given question,

Q: Explain what is meant when we say that a quantitative predictor variable and a qualitative predictor…

A:

Q: What are the functional forms of the regression model? Explain.

A: A functional form refers to the algebraic form of a relationship between a dependent variable and…

Q: The overall purpose of regression analysis is:

A: There are two major purpose of regression analysis.  i. To predict outcome variable by using the…

Q: Explain the value of the coefficient of determination and the overall significance of the model.

A: Given,  Q = f( P, M, PR) where Qc = demand for cement/month (in yards), Pc = the price of cement per…

Q: how are correlation and regression analysis used in research?

A: Given : Corr. : Variables are said to be correlated , when change in one var.  affect the change(e)…

Q: Explain what secondary analysis is and its key advantages and disadvantages

A:

Q: What is basic regression? What is multiple regression? How do they both relate to Data Mining?

A: Independent and dependent variables in regression: In a simple regression, the variable of interest,…

Q: Explain Univariate Analysis?

A: Univariate Analysis is the analysis of variable. As the name suggests 'uni' means one i.e analysis…

Q: Define Multiple Regression?

A: Regression It is used to describe connection between a response variable and one or more regressors

Q: Importance of Data Analysis in Research

A: Explain.... Importance of Data Analysis in Research.

Q: What is correlation and multiple regression,discuss their uses in data analysis

A: Correlation and Regression are the fundamental concepts of statistics.

Q: What are the Cautions in Regression Analysis?

A: Regression analysis is a set of statistical methods used for the estimation of relationships between…

Q: How does linear regression differ from analysis of variance?

A: 1.) ANOVA and Linear Regression, both are almost the same thing but the key difference is, Preferred…

Q: Differentiate Regrassion analysis and Correlational analysis?

A:

Q: distinguish between the unit of analysis and the aggregates?

A: The unit of analysis refers to the major parameter that is being investigated in study. The obvious…

Q: Illustrate the importance of using regression models.

A: What is Regression Analysis ?  Regression analysis is a method of mathematically sorting out which…

Q: Briefly describe what is meant by the problem of errors in measurement of the predictor variables…

A: Errors in Measurement:

Q: What is the difference between ordinary least-squares regression analysis and multiple…

A: The model for ordinary least square regression analysis is: xi are k explanatory variables and y is…

Q: What are some important applications of regression analysis in the real world?

A: 1.)Weather forecast    2.)Financial Risk and growth assessment   3.)Analysis of medical data…

Q: Summarize

A: Qualitative research is defined as research that uses methodologies like participant observation or…

Q: Explain how using multiple linear regression controls for confounding.

A: we know that multiple linear regression is the extension of simple linear regression .as simple…

Q: Discuss the differences between quantitative and qualitative data, as well as the advantages and…

A: Any information is termed to be data, depending upon the characteristics it is of two types…

Q: Explain the Theory of Multiple Regression Analysis?

A: Regression analysis is a powerful statistical method that allows you to examine the…

Q: What is Data Mining? Justify the use of data mining to support the use of multiple regression.

A: Data mining is the process of finding the hidden, valid and potentially useful patterns in the huge…

Q: Explain how a restricted region of values of the predictor variables can affect our understanding of…

A: Restricted values of predictor variable:In a dataset, the available values of the predictor variable…

Q: What is the variable requirement for a chi-square analysis?

A: The Chi-Square Test specifies whether categorical variables are correlated (i.e., whether the…

Q: How does the general classification problem discussed in Section 17-3 differ from the general…

A: How does a generalized classification problem differ from a generalized problem analyzed with…

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related. 

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.