100% Zufriedenheitsgarantie Sofort verfügbar nach Zahlung Sowohl online als auch als PDF Du bist an nichts gebunden
logo-home
Summary- Advanced Quantitative Research Methods (INFOQNM) 7,66 €   In den Einkaufswagen

Zusammenfassung

Summary- Advanced Quantitative Research Methods (INFOQNM)

 33 mal angesehen  3 mal verkauft
  • Kurs
  • Hochschule

This document is a summary of all lectures and lecture notes, with extra notes, incuding clear figures and additional explanations of statistical tests and theories. It also includes the quizzes with answers (in the footnote) All you need for the exam :)

vorschau 4 aus 125   Seiten

  • 12. juni 2024
  • 125
  • 2023/2024
  • Zusammenfassung
avatar-seller
Advanced Quantitative Research Methods

Lecture 1 – Introduction
• Quantitative research quantifies relationships between observable measures of a
theoretical construct
• Example: Using Heart Rate, Blood Pressure, and self-reported stress surveys to
measure the construct cardiovascular health or stress
• This sounds vague…but life is chaotic

Nomological networks










Introduction to quantitative research
• Theoretical construct: The construct you want to measure (e.g., age, stress, sleep
quality)
• Measure: the construct you want to measure (e.g., age, stress, sleep quality)
• Operationalisation: Translation of a somewhat vague construct to a precise
measurement (e.g., how, what, why, type, scale)
• Variable: Outcome of applying the measure, the actual ‘data’ (e.g., heart rate, hapiness
score)
• Q: Which of the following is a measure? (A)Heart rate b) Stress level c) Pittsburg Sleep
Questionnaire d) Question type)1


1 Answer: c) Pitssburgh Sleep Questionnaire

1

,Scales
• Nominal: Categorical variables where order makes no sense
o Type of transport, mood, breakfast
• Ordinal: Categorical variables where order makes (some) sense
o Income levels, pain intensity, (Likert scales)
• Interval: No natural zero value, but differences make sense
o The zero is a starting point, but it doesn't mean there's none of something; it's
more of a benchmark.
o Temperature, IQ scores, pH levels, (Likert scales)
• Ratio: Natural zero value. Ratios and differences make sense
o The zero means there's none of something, and you can also compare amounts
and see how many times one amount is bigger than another.
o Heart rate, respiration, blood pressure
• Q: I measure your level of attention using the duration (in seconds) you look at your
phone instead of me. What scale does my variable have?2

Variables
• Various types:
o Continuous: Can also have a value between two other values
o Discrete: Only distinct values are possible
• Various roles:
o Independent: Predictors; X; the ‘knobs’ used to explain
o Dependent: Outcome; Y; the observed variable to explain

Quality
• How precise are our measurements? (i.e., how reliable/consistent?)
• How accurate are our measurements? (i.e., how valid?)
• High reliability but low validity = bad (Headsize to measure intelligence)
• Low reliability but high validity = bad (Scale 0-10, how happy are you right now?)
• High reliability and high validity = good! (Balanced and validated questionnaire for sleep
quality, PSQI)
• Reliability (precise)
o Test-retest: If repeated later, do we get the same answer?
o Inter-rater: If repeated for someone else, do we get the same answer?
o Parallel forms: If repeated across theoretically equivalent but different
measurements, do we get the same answer?
o Internal consistency: Do the different parts of a questionnaire agree with each
other?
• Q: I measure my stress level using a self-reported survey with multiple questions. I do
this twice using different survey’s. What type(s) of reliability are assessed here?3
• Validity (accuracy)
o Many types
o Construct validity: To what extent do the measurements allow us to make
conclusions about the theoretical construct?

2 Ratio
3 Parallel forms and internal consistency

2

, ▪ High validity example: Continuous report of affect
▪ Low validity example: HR to estimate stress
o Ecological validity: To what extent do the conclusions generalize to real-world
situations?
▪ High validity example: TIHM dataset (recorded at home)
▪ Low validity example: CASE dataset (recorded in restricted lab setting)
• Threats to validity
o Confound: Additional unmeasured variable related to the predictors and
outcomes
o Artifact: Special situation during your study that limits generalizability
o Many types of confounds and artifacts…
o History effects: Specific (historic) events occured that influence outcomes
o Maturational effects: People age, getting bored, tired, etc…
o Repeated testing: People learn and practice, getting familiar
o Selection bias: Treatment and control group have different characteristics
o Non-response bias: People responding have more in common than random
o Experimenter bias: Asking specific questions, signaling desired behaviour
o Demand effects: The fact that people know they are part of an experiment can
influence their behavior or responses.
o Placebo effects: Control group shows effect
o Fraud, deception, self-deception, etc…: Researcher dishonesity
• Ultimate goal of good research design: Maximise validity and reliability by minimizing
threats.




3

, Lecture 2 – Parametric vs Non-Parametric tests (1/3)
Statistical inference
• You are a teacher at Hogwarts. You want to know what percentage of students can
perform a Patronus charm to adapt your lectures.
• You have a population.
• You have a parameter you want to know.
• You need to take a sample of Hogwarts students to estimate the variable.
• How do you know if the estimation for the parameter you get from the sample is
accurate for the whole population?
o → Statistical inference: infer properties (draw conclusions) from a sample
about the population
• Greek letters = population; normal alphabet = sample

Parametric vs non parametric tests
• Statistical tests: parametric or non-parametric?
• Parametric tests assume a specific distribution for the data of the population.
• Parametric tests are more powerful when these assumptions are met. Non-
parametric tests are more robust when these assumptions are violated.




4

Alle Vorteile der Zusammenfassungen von Stuvia auf einen Blick:

Garantiert gute Qualität durch Reviews

Garantiert gute Qualität durch Reviews

Stuvia Verkäufer haben mehr als 700.000 Zusammenfassungen beurteilt. Deshalb weißt du dass du das beste Dokument kaufst.

Schnell und einfach kaufen

Schnell und einfach kaufen

Man bezahlt schnell und einfach mit iDeal, Kreditkarte oder Stuvia-Kredit für die Zusammenfassungen. Man braucht keine Mitgliedschaft.

Konzentration auf den Kern der Sache

Konzentration auf den Kern der Sache

Deine Mitstudenten schreiben die Zusammenfassungen. Deshalb enthalten die Zusammenfassungen immer aktuelle, zuverlässige und up-to-date Informationen. Damit kommst du schnell zum Kern der Sache.

Häufig gestellte Fragen

Was bekomme ich, wenn ich dieses Dokument kaufe?

Du erhältst eine PDF-Datei, die sofort nach dem Kauf verfügbar ist. Das gekaufte Dokument ist jederzeit, überall und unbegrenzt über dein Profil zugänglich.

Zufriedenheitsgarantie: Wie funktioniert das?

Unsere Zufriedenheitsgarantie sorgt dafür, dass du immer eine Lernunterlage findest, die zu dir passt. Du füllst ein Formular aus und unser Kundendienstteam kümmert sich um den Rest.

Wem kaufe ich diese Zusammenfassung ab?

Stuvia ist ein Marktplatz, du kaufst dieses Dokument also nicht von uns, sondern vom Verkäufer IsabelleU. Stuvia erleichtert die Zahlung an den Verkäufer.

Werde ich an ein Abonnement gebunden sein?

Nein, du kaufst diese Zusammenfassung nur für 7,66 €. Du bist nach deinem Kauf an nichts gebunden.

Kann man Stuvia trauen?

4.6 Sterne auf Google & Trustpilot (+1000 reviews)

45.681 Zusammenfassungen wurden in den letzten 30 Tagen verkauft

Gegründet 2010, seit 14 Jahren die erste Adresse für Zusammenfassungen

Starte mit dem Verkauf
7,66 €  3x  verkauft
  • (0)
  Kaufen