100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Summary Quantitative and Design Methods in Business Research () $7.27   Add to cart

Summary

Summary Quantitative and Design Methods in Business Research ()

 13 views  2 purchases
  • Course
  • Institution

Summary about everting you need. I got an 8.9 due to this summary alone.

Preview 3 out of 22  pages

  • January 18, 2024
  • 22
  • 2023/2024
  • Summary
avatar-seller
Quantitative and Design Methods in Business Research


Table of contents
Factor analysis ...............................................................................................................................................2
Lecture 1 Introduction.........................................................................................................................................2
Design & behavioral research ............................................................................................................................4
Lecture 2 Principal Component Analysis and Exploratory Factor Analysis ......................................................5
Discussion Factor Analysis.................................................................................................................................8

Regression Analysis .......................................................................................................................................8
Guest lecture .......................................................................................................................................................8
Lecture regression analysis ...............................................................................................................................10
Discussion Regression Analysis ........................................................................................................................13

ANOVA ........................................................................................................................................................13
Lecture ANOVA (Analysis of CoVariance) ........................................................................................................13

Structural Equation Modeling .....................................................................................................................16
Lecture SEM .....................................................................................................................................................16




1

,Factor analysis
Lecture 1 Introduction
Multivariate data analysis comprises all statistical methods that simultaneously analyze
multiple measurements on each individual or object under investigation. Motivation for using
this are measurement, explanation and prediction, and hypothesis testing.
Basic concepts are measurement scales (nonmetric and metric),
measurement and measurement error, statistical inference and
types of techniques.

Measurement scales:
• Nonmetric measures qualitative characteristics of variables
o Nominal: size of number is not related to the
amount of the characteristic being measured
§ Gender, colour
o Ordinal: larger numbers indicate more (or less) of
the characteristics measured, but not how much
more (or less)
§ Type of residence, category of vehicle
• Metric measures quantitative characteristics or variables
o Interval: contains ordinal properties, and in addition, there are equal
differences between scale points
§ Temperature in Celcius, IQ scale
o Ratio: contains interval scale properties, and
in addition, there is a natural zero point
§ Body height, monthly income

Measurement error distorts observed relationships and makes
multivariate techniques less powerful. All variables have some error.
Researchers have summated scales, for which several variables are
summed or averaged together to form a composite representation of a
concept. The higher the measurement error, the smaller the beta.
In addressing measurement error, researchers evaluate two important
characteristics of measurement:
• Reliability: the observed variable’s degree of precision
(reproducibility of results) and thus the lack of random
measurement error
• Validity: the degree to which a measure accurately represents
what it is supposed to

Statistical significance and power:
• Type 1 error, or alfa, is the probability of rejecting
the null hypothesis when it is true. Null hypothesis
is usually that there is no effect. Severe in
management studies because you could lose money
if you invest while there is no effect.
• Type 2 error, or beta, is the probability of failing to reject the null hypothesis when it
is false. You miss an effect, less severe in management studies because you do not lose
money.




2

, • Power, or 1-beta, is the probability of rejecting the null hypothesis when it is false.
Power is the probability that a test of significance will detect a deviation from the null
hypothesis, should such a deviation exist.
• Effect size: the actual magnitude of the effect of interest. The difference between
means or the correlations between variables.
• Alpha (a): is the level of significance. As a is set at smaller levels, power decreases.
Typically a=0.05
• Sample size: as sample size increases, power increases. With very large sample sizes,
even very small effects can be statistically significant, raising the issue of practical
significance versus statistical significance.
Effect size, alpha and sample size are all related.

Statistical power analysis:
• Researchers should design the study to achieve a power level of 0.80 at the desired
significance level.
• More stringent significance levels (0.01 versus 0.05) require larger samples to achieve
the desired power level
• Power can be increased by choosing a less stringent alpha level.
• Smaller effect sizes always require larger sample sizes to achieve the desired power.
• Any increase in power is most likely achieved by increased sample size.

Types of multivariate techniques:
• Dependence techniques: a variable or set of variables is identified as the dependent
variable to be predicted or explained by other variables knows as independent
variables.
o Multiple regression, ANOVA, Structural Equation Modeling (SEM)
• Interdependence techniques: they involve the simultaneous analysis of all variables in
the set, without distinction between dependent and independent variables.
o Exploratory factor analysis, Principal component analysis

Factor analysis analyzes the structure of the interrelationships among a large number of
variables to determine a set of common underlying dimensions (factors).
Multiple regression: a single metric dependent variable is predicted by several metric
independent variables.
Analysis of Variance (ANOVA): a metric dependent variable is predicted by a set of
nonmetric (categorical) independent variables.
Structural Equation Modeling (SEM) estimates multiple, interrelated dependence
relationships based on components: structural model and measurement model.

Guidelines for multivariate analysis: establish practical significance (is it important?) as well
as statistical significance, sample size affects all results, know your data, strive for model
parsimony (do not make it too complicated), look at your errors and validate your results.

A structured approach to multivariate model building:
1. Define the research problem, objectives, and multivariate techniques to be used.
2. Develop the analysis plan
3. Evaluate the assumptions underlying the multivariate techniques
4. Estimate the multivariate model and assess overall model fit
5. Interpret the coefficients
6. Validate the multivariate model

3

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller masterbastudent. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $7.27. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

83662 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 14 years now

Start selling
$7.27  2x  sold
  • (0)
  Add to cart