Samenvattingen voor statistiek, onderzoeksmethoden en SPSS?

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Table of related content to: Samenvattingen voor statistiek, onderzoeksmethoden en SPSS
Intro

Wat is statistiek?

  • Statistiek is de wetenschap van kennis opdoen op basis van data. Data zijn numerieke (of kwalitatieve) beschrijvingen en gegevens van objecten om te bestuderen (Moore & McCabe)

Wat zijn onderzoeksmethoden?

  • Om verschijnselen in de sociale werkelijkheid op een systematische manier te ordenen, maakt men gebruik van methoden. Technieken zijn over het algemeen een klein onderdeel van een methode, bijvoorbeeld een steekproeftechniek die wordt gebruikt om een enquête te maken.
  • Bij kwantitatief onderzoek worden theorieën getoetst aan de hand van (grote hoeveelheden) data, bij kwalitatief onderzoek ligt de focus meer op de kwaliteit en diepgang van het onderzoek, en kunnen er nieuwe theorieën voortvloeien uit het onderzoek. (Bryman)

Wat is SPSS Statistics?

  • SPSS is een statistisch computerprogramma dat door wetenschappers wordt gebruikt om gegevens te verzamelen, analyseren en te bewerken. Het wordt voornamelijk gebruikt om onderzoeksresultaten te onderzoeken.
  • De afkorting SPSS staat voor Statistical Package for the Social Sciences. Het programma wordt dus met name in de sociale wetenschap gebruikt.

Samenvattingen en studiehulp voor statistiek

  • zie hieronder

   

More supporting content:
Statistics: Magazines for understanding statistics

Statistics: Magazines for understanding statistics

Startmagazine: Introduction to Statistics

Startmagazine: Introduction to Statistics

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Introduction to Statistics: in short

  • Statistics comprises the arithmetic procedures to organize, sum up and interpret information. By means of statistics you can note information in a compact manner.
  • The aim of statistics is twofold: 1) organizing and summing up of information, in order to publish research results and 2) answering research questions, which are formed by
........Read more
Understanding data: distributions, connections and gatherings
Understanding reliability and validity
Statistics Magazine: Understanding statistical samples
Understanding distributions in statistics
Understanding variability, variance and standard deviation
Understanding inferential statistics
Understanding type-I and type-II errors
Understanding effect size, proportion of explained variance and power of tests to your significant results
Statistiek: samenvattingen en studiehulp - Thema
Statistics: Magazines for encountering Statistics

Statistics: Magazines for encountering Statistics

Startmagazine: Introduction to Statistics

Startmagazine: Introduction to Statistics

Image

Introduction to Statistics: in short

  • Statistics comprises the arithmetic procedures to organize, sum up and interpret information. By means of statistics you can note information in a compact manner.
  • The aim of statistics is twofold: 1) organizing and summing up of information, in order to publish research results and 2) answering research questions, which are formed by
........Read more
Stats for students: Simple steps for passing your statistics courses

Stats for students: Simple steps for passing your statistics courses

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How to triumph over the theory of statistics (without understanding everything)?

Stats of students

  • The first years that you follow statistics, it is often a case of taking knowledge for granted and simply trying to pass the courses. Don't worry if you don't understand everything right away: in later years it will fall into place, and you will see the importance of the theory you had to know before.
  • The book you need to study may be difficult to understand at first. Be patient: later in your studies, the effort you put in now will pay off.
  • Be a Gestalt Scientist! In other words, recognize that the whole of statistics is greater than the sum of its parts. It is very easy to get hung up on nit-picking details and fail to see the forest because of the trees
  • Tip: Precise use of language is important in research. Try to reproduce the theory verbatim (i.e. learn by heart) where possible. With that, you don't have to understand it yet, you show that you've been working on it, you can't go wrong by using the wrong word and you practice for later reporting of research.
  • Tip: Keep study material, handouts, sheets, and other publications from your teacher for future reference.

How to score points with formulas of statistics (without learning them all)?

  • The direct relationship between data and results consists of mathematical formulas. These follow their own logic, are written in their own language, and can therefore be complex to comprehend.
  • If you don't understand the math behind statistics, you don't understand statistics. This does not have to be a problem, because statistics is an applied science from which you can also get excellent results without understanding. None of your teachers will understand all the statistical formulas.
  • Please note: you will probably have to know and understand a number of formulas, so that you can demonstrate that you know the principle of how statistics work. Which formulas you need to know differs from subject to subject and lecturer to lecturer, but in general these are relatively simple formulas that occur frequently, and your lecturer will likely tell you (often several times) that you should know this formula.
  • Tip: if you want to recognize statistical symbols, you can use: Recognizing commonly used statistical symbols
  • Tip: have fun with LaTeX! LaTeX code gives us a simple way to write out mathematical formulas and make them look professional. Play with LaTeX. With that, you can include used formulas in your own papers and you learn to understand how a formula is built up – which greatly benefits your understanding and remembering that formula. See also (in Dutch): How to create formulas like a pro on JoHo WorldSupporter?
  • Tip: Are you interested in a career in sciences or programming? Then take your formulas seriously and go through them again after your course.

How to practice your statistics (with minimal effort)?

How to select your data?

  • Your teacher will regularly use a dataset for lessons during the first years of your studying. It is instructive (and can be a lot of fun) to set up your own research for once with real data that is also used by other researchers.
  • Tip: scientific articles often indicate which datasets have been used for the research. There is a good chance that those datasets are valid. Sometimes there are also studies that determine which datasets are more valid for the topic you want to study than others. Make use of datasets other researchers point out.
  • Tip: Do you want an interesting research result? You can use the same method and question, but use an alternative dataset, and/or alternative variables, and/or alternative location, and/or alternative time span. This allows you to validate or falsify the results of earlier research.
  • Tip: for datasets you can look at Discovering datasets for statistical research

How to operationalize clearly and smartly?

  • For the operationalization, it is usually sufficient to indicate the following three things:
    • What is the concept you want to study?
    • Which variable does that concept represent?
    • Which indicators do you select for those variables?
  • It is smart to argue that a variable is valid, or why you choose that indicator.
  • For example, if you want to know whether someone is currently a father or mother (concept), you can search the variables for how many children the respondent has (variable) and then select on the indicators greater than 0, or is not 0 (indicators). Where possible, use the terms 'concept', 'variable', 'indicator' and 'valid' in your communication. For example, as follows: “The variable [variable name] is a valid measure of the concept [concept name] (if applicable: source). The value [description of the value] is an indicator of [what you want to measure].” (ie.: The variable "Number of children" is a valid measure of the concept of parenthood. A value greater than 0 is an indicator of whether someone is currently a father or mother.)

How to run analyses and draw your conclusions?

  • The choice of your analyses depends, among other things, on what your research goal is, which methods are often used in the existing literature, and practical issues and limitations.
  • The more you learn, the more independently you can choose research methods that suit your research goal. In the beginning, follow the lecturer – at the end of your studies you will have a toolbox with which you can vary in your research yourself.
  • Try to link up as much as possible with research methods that are used in the existing literature, because otherwise you could be comparing apples with oranges. Deviating can sometimes lead to interesting results, but discuss this with your teacher first.
  • For as long as you need, keep a step-by-step plan at hand on how you can best run your analysis and achieve results. For every analysis you run, there is a step-by-step explanation of how to perform it; if you do not find it in your study literature, it can often be found quickly on the internet.
  • Tip: Practice a lot with statistics, so that you can show results quickly. You cannot learn statistics by just reading about it.
  • Tip: The measurement level of the variables you use (ratio, interval, ordinal, nominal) largely determines the research method you can use. Show your audience that you recognize this.
  • Tip: conclusions from statistical analyses will never be certain, but at the most likely. There is usually a standard formulation for each research method with which you can express the conclusions from that analysis and at the same time indicate that it is not certain. Use that standard wording when communicating about results from your analysis.
  • Tip: see explanation for various analyses: Introduction to statistics
Statistics: Magazines for applying statistics

Statistics: Magazines for applying statistics

Applying z-tests and t-tests
Applying correlation, regression and linear regression
Applying spearman's correlation
Applying multiple regression
Statistiek: samenvattingen en studiehulp - Thema
Statistiek: samenvattingen en studiehulp - Thema

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Latest changes and updates tagged with: Samenvattingen voor statistiek, onderzoeksmethoden en SPSS

Studiegids voor samenvattingen bij Research Methods in Psychology: Evaluating a World of Information van Morling

Studiegids met samenvattingen en studiehulp voor:

  • Boektitel: Research Methods in Psychology
  • Subtitel: Evaluating a World of Information
  • Auteur: Morling
  • Druk: 4e druk en 3e druk

Waar gaat 'Research Methods in Psychology' over?

  • Dit boek is een uitgebreide gids voor onderzoeksmethoden in de psychologie. Het behandelt verschillende onderzoeksontwerpen, data-analysetechnieken en hoe je wetenschappelijke informatie kritisch kunt evalueren.
  • Je leert hoe je zelf psychologisch onderzoek kunt uitvoeren en hoe je de resultaten van andermans onderzoek kunt interpreteren. Je krijgt inzicht in de wetenschappelijke methode en leert hoe je wetenschappelijke claims kunt beoordelen.

Wanneer kan je 'Research Methods in Psychology' goed gebruiken?

  • Dit boek is geschreven voor studenten psychologie die een inleiding tot onderzoeksmethoden nodig hebben. Het is ook handig voor iedereen die geïnteresseerd is in het begrijpen van hoe psychologisch onderzoek werkt.
  • De kennis uit dit boek kan worden ingezet bij uiteenlopende beroepen in de
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Studiegids voor samenvattingen bij Introduction to and application of research methods and statistics Custom UU editie van Morling en Carr

Studiegids met samenvattingen en studiehulp voor:

  • Boektitel: Introduction to and application of research methods and statistics
  • Auteurs: Morling en Carr
  • Druk: 1e UU druk

Over het boek

Het boek 'Introduction to and application of research methods and statistics' is een boek dat speciaal voor de Universiteit Utrecht is samengesteld. Het is gebaseerd op twee andere boeken:

  • Research Methods (Beth Morling, 4e druk)
  • The Art and Science of Social Research (Deborah Carr e.a., 2e druk)

Dat dit boek een compilatie is van twee andere boeken, zie je ook duidelijk terug in de opbouw van het boek. In dit boek zijn de originele hoofdstuknummers behouden, dus het volgt geen logische structuur, maar gaat van 1-2-3-7-10-11 [..] terug naar 4 enzovoort. In de samenvatting en studiehulp is ervoor gekozen deze volgorde te volgen.

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Samenvattingen en stappenplannen bij SPSS (versie 24) - Bundel

Deze bundel bevat samenvattingen en stappenplannen bij de meestgebruikte onderdelen en analyses van SPSS en is gebaseerd op de 24e versie.

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Onderzoeksmethoden - Scheepers e.a. - Boeksamenvatting 7e druk

Hoofdstuk 1 Introductie: wetenschap als communicatieproces

Wetenschap is te zien als een systematisch geheel van kennis. Om een systematische samenhang tijdens onderzoek te krijgen maken wetenschappers gebruik van een aantal methoden en technieken.

Er zijn twee typen wetenschappelijk onderzoek. Het eerste type is fundamenteel wetenschappelijk onderzoek en wil wetenschappelijke kennis uitbreiden. Praktijkgericht wetenschappelijk onderzoek is gericht op de ontwikkeling, uitvoering en evaluatie van oplossingen die

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What is statistics?

What is statistics?

Statistics is the science of data, encompassing its collection, analysis, interpretation, and communication to extract knowledge and inform decision-making.

This definition focuses on the core aspects of the field:

  • Data-driven: Statistics revolves around analyzing and interpreting data, not just manipulating numbers.
  • Knowledge extraction: The goal is to gain insights and understanding from data, not just generate summaries.
  • Decision-making: Statistics informs and empowers informed choices in various settings.

Statistics has a wide application:

1. Design and Inference:

  • Designing studies: Statisticians use statistical principles to design experiments, surveys, and observational studies that allow for reliable inferences.
  • Drawing conclusions: Statistical methods help estimate population parameters from sample data, accounting for uncertainty and variability.

2. Modeling and Analysis:

  • Identifying relationships: Statistical models reveal patterns and relationships among variables, aiding in understanding complex systems.
  • Quantitative analysis: Various statistical techniques, from regression to machine learning, enable deep analysis of data structures and trends.

3. Interpretation and Communication:

  • Meaningful conclusions: Statisticians go beyond numbers to draw meaningful and context-specific conclusions from their analyses.
  • Effective communication: Clear and concise communication of findings, including visualizations, is crucial for informing stakeholders and advancing knowledge.

Applications across disciplines:

These core principles of statistics find diverse applications in various academic fields:

  • Social sciences: Understanding societal patterns, testing hypotheses about human behavior, and evaluating policy interventions.
  • Natural sciences: Analyzing experimental data, modeling physical phenomena, and drawing inferences about natural processes.
  • Business and economics: Forecasting market trends, evaluating business strategies, and guiding investment decisions.
  • Medicine and public health: Analyzing clinical trials, identifying risk factors for disease, and informing healthcare policies.

Ultimately, statistics plays a crucial role in numerous academic disciplines, serving as a powerful tool for extracting knowledge, informing decisions, and advancing human understanding.

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