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T-Test in Parametric Tests (with Finance Examples)

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  The t-test is a parametric statistical test used to determine whether there is a significant difference between the means of two groups, assuming the data follows a normal distribution and the population variance is unknown.  Types of t-tests: Type Purpose Example in Finance One-sample t-test Compares sample mean to a known value Test if the average return of a mutual fund is significantly different from the market’s average return (e.g., Nifty 50 annual return of 12%). Two-sample independent t-test Compares means of two independent groups Compare the average returns of two different portfolios (e.g., a growth fund vs. a value fund). Paired-sample t-test Compares means from the same group at different times Compare a company's stock return before and after a major policy change or merger.  Example 1: One-Sample t-test in Finance P...

Is Likert scale data suitable for parametric tests?

 Great question—and it's a common debate in research, including finance. Let’s break it down and then explain it with a finance-related example .  What is a Likert Scale? A Likert scale typically measures attitudes or perceptions using options like: Strongly Disagree – Disagree – Neutral – Agree – Strongly Agree → These are ordinal (ordered, but not necessarily equal spacing).  Parametric Tests Need Interval Data: ·          Parametric tests (e.g., t-test, ANOVA, regression) assume interval or ratio data —where differences between values are meaningful and consistent . ·          Ordinal data doesn't meet this strict requirement.  The Debate: ·          Technically : Likert scale data is ordinal , not interval. ·          Practically : When Likert scales have 5 or more points , researche...

Understanding Type I and Type II Error in context of Finance

  Absolutely! Let's use a finance-related example to explain:  Context: A Company’s New Investment Strategy Let’s say a company is testing a new investment strategy and wants to know if it gives better returns than the current strategy.  Null Hypothesis (H₀): “The new investment strategy gives no better return than the old strategy.”  Two possible mistakes explained in finance terms: 1 Rejecting a True Null Hypothesis (Type I Error) 📌 You conclude: “The new strategy gives better returns.” 📉 But in reality: The new strategy is not better . 🔴 What happens? You switch to the new strategy thinking it’s better, but actually lose money or perform worse. 💼 Financial impact: Wasted resources, opportunity loss, maybe even real monetary loss. 2  Failing to Reject a False Null Hypothesis (Type II Error) 📌 You conclude: “The new strategy is not better, so we won’t use it.” 📈 But in reality: The new strategy actually is better. ...

30 interview questions with answers on Descriptive and Inferential Statistics

 Here are 30 interview questions with answers on Descriptive and Inferential Statistics , organized into relevant categories to help students, researchers, and job seekers in analytics, finance, research, or data science fields: 🔹 A. Basics & Definitions (1–10) What is descriptive statistics? Descriptive statistics summarize and organize features of a data set using measures such as mean, median, mode, standard deviation, and graphs . What is inferential statistics? Inferential statistics involve drawing conclusions about a population based on a sample through hypothesis testing, confidence intervals, and regression analysis . What are the major types of descriptive statistics? Measures of central tendency : Mean, Median, Mode Measures of dispersion : Range, Variance, Standard Deviation Shape : Skewness, Kurtosis What are the main tools used in inferential statistics? Hypothesis testing Confidence intervals t-tests, z-tests ANOVA Ch...

30 interview questions with answers on EViews (Econometric Views)

 Here are 30 interview questions with answers on EViews (Econometric Views) specifically used in finance research , categorized for clarity and ease of use in interviews or academic training: 🔹 A. Basics of EViews in Finance (1–10) What is EViews? EViews is an econometrics and statistical software used for time series analysis, forecasting, panel data analysis , and econometric modeling , especially in finance and economics . Which file formats are used in EViews? EViews uses .wf1 (workfile) for project files and can import Excel, CSV, text, and STATA files . What kind of data is used in EViews for finance research? Mostly time series , cross-sectional , and panel data like stock prices, returns, GDP, exchange rates, etc. Can EViews handle panel data? Yes, EViews supports panel data regression , including fixed effects, random effects, and dynamic panels. Why is EViews preferred in finance research? It provides advanced econometric modeling , macroeconom...

30 interview questions with answers on SPSS (Statistical Package for the Social Sciences)

 Here are 30 interview questions with answers on SPSS (Statistical Package for the Social Sciences) commonly used in research, organized thematically: 🔹 A. Basics of SPSS (1–10) What is SPSS? SPSS is a software package used for statistical analysis in social science, business, health, and education research . What types of data can SPSS handle? SPSS can handle nominal, ordinal, interval, and ratio scale data. What are the two main views in SPSS? Data View : Shows raw data in spreadsheet format Variable View : Used to define variables, types, labels, values, and measurement levels. How do you define a variable in SPSS? In Variable View , you can assign a name, type, label, value labels , and measurement level . What file extension does SPSS use to save data? SPSS saves data files with the extension .sav . What is a syntax file in SPSS? A file containing SPSS commands written in syntax language. File extension: .sps . What is the Output Viewe...

30 interview questions with answers on SmartPLS

 Here are 30 interview questions with answers on SmartPLS used in research, categorized for better understanding: 🔹 A. Basics of SmartPLS and PLS-SEM (1–10) What is SmartPLS? SmartPLS is a software tool used for Partial Least Squares Structural Equation Modeling (PLS-SEM) , allowing researchers to analyze complex cause-effect relationship models with latent variables. What is PLS-SEM? Partial Least Squares Structural Equation Modeling is a variance-based SEM technique ideal for predictive modeling and handling small sample sizes and non-normal data . What type of data is suitable for PLS-SEM? PLS-SEM works well with non-normal data , small to medium sample sizes , and exploratory research . When should one use SmartPLS instead of CB-SEM? Use SmartPLS when the objective is prediction , the model is complex , the sample size is small , or the data is not normally distributed . What are the key components of a PLS-SEM model? Measurement model (outer model...