This article discusses research and statistical methods for businesses to collect, store, analyze and interpret data to make informed management decisions. It covers topics such as sample size, sampling method, measures of variables, collection of data on social demographics and research design. The article uses a case study to illustrate the concepts discussed.

Associations between Quantitative and Qualitative Job Insecurity and Well-being

Investigating the association between employee's perception of quantitative and qualitative job insecurity with job satisfaction and psychological distress in the Belgium banking sector.

Discover how businesses use research and statistics to gather, analyze, and interpret data for informed decision-making. Covers sampling, variables, demographics, and research design.

Research and Statistical Method for Business | Desklib

Research and Statistical Method for Business

This paper investigates the methodology used in business research with a case study of De Witte et al. (2010) who investigated the association of employee’s perception of quantitative and qualitative job insecurity with job satisfaction, and psychological distress in the Belgium banking sector.

Hartpury University and Hartpury College

Data Science and Big Data

This article explains the concepts of Alternative Hypothesis, Confidence Interval, Sample Estimate and P Value in Statistics. It also provides two approaches to interpret the given results - P value approach and Confidence Interval approach.

Statistics and Probability

Understanding Alternative Hypothesis, Confidence Interval, Sample Estimate and P Value in Statistics

This article presents a statistical analysis on the average annual expenditure on housing and electricity in USA. It includes the confidence interval for housing expenditure and hypothesis testing for electricity expenditure based on marital status.

Statistical Analysis on Housing and Electricity Expenditure in USA

This article explains the assumptions and key concepts of Pearson linear correlation test, including the T statistic, degree of freedom, p value, alternative hypothesis, 95% confidence interval, and sample estimate. It also discusses the rejection of null hypothesis through the p value and confidence interval approach.

Pearson Linear Correlation Test: Assumptions and Key Concepts

This article presents a statistical analysis of the diameter of a product using hypothesis testing and confidence intervals. It includes sample mean, standard deviation, t-statistic, p-value, confidence interval, and minimum sample size. The article concludes that the diameter of the product is different from the intended 0.75 inch. It also discusses the altered hypotheses and the type of test used.

Research and Statistical Method for Business

About This Document

Research and Statistical Method for Business

Understanding Alternative Hypothesis, Confidence Interval, Sample Estimate and P Value in Statistics

Statistical Analysis on Housing and Electricity Expenditure in USA

Pearson Linear Correlation Test: Assumptions and Key Concepts

Statistical Analysis of Diameter of a Product

QAB 105 Assignment On Quantitative Analysis for Business

Research and Statistical Method for Business

About This Document

Research and Statistical Method for Businesslg...

Understanding Alternative Hypothesis, Confidence Interval, Sample Estimate and P Value in Statisticslg...

Statistical Analysis on Housing and Electricity Expenditure in USAlg...

Pearson Linear Correlation Test: Assumptions and Key Conceptslg...

Statistical Analysis of Diameter of a Productlg...

QAB 105 Assignment On Quantitative Analysis for Businesslg...

Research and Statistical Method for Business

Understanding Alternative Hypothesis, Confidence Interval, Sample Estimate and P Value in Statistics

Statistical Analysis on Housing and Electricity Expenditure in USA

Pearson Linear Correlation Test: Assumptions and Key Concepts

Statistical Analysis of Diameter of a Product

QAB 105 Assignment On Quantitative Analysis for Business