100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Previously searched by you
Previously searched by you
logo
Introduction to Statistics Lecture notes January 2023 $6.09
Add to cart
Quickly navigate to
Preview
  2.  
  3. Universiteit Van Amsterdam (UvA)
  4.  
  5. Introduction to Statistics

Class notes

Introduction to Statistics Lecture notes January 2023
 0 purchase
  • Course
  • Introduction to Statistics
  • Institution
  • Universiteit Van Amsterdam (UvA)

Exam grade: 9.1 Complete notes from all Introduction to Statistics lectures with all pictures from slides, with nice aesthetics and a beautiful purple layout. I got a high grade from an exam so I guess the notes are helpful :)

Preview 3 out of 29  pages

Document information

  • March 20, 2023
  • 29
  • 2022/2023
  • Class notes
  • Thijs bol
  • All classes

Subjects

  • stats
  • statistics
  • intro to statistics
  • lectures
  • math
  • introduction to statistics

Written for

  • Universiteit van Amsterdam (UvA)
  • Sociologie
  • Introduction to Statistics
All documents for this subject (9)

Seller

avatar-seller
juliaradzieta

Reviews received

Content preview

ӯ yi ŷ s σ μ ± √ μ0 H0 Ha ≠ →


Lecture 1
Week 1: inferential statistics

● How do we draw conclusions about a population from a sample?
● Key concepts: probability, empirical rule, sample, population, sampling
distribution, standard error, confidence interval, central limit theorem,

➢ Types of variables
○ different types of variables require different types of description




➢ Core function of statistics is to describe data
○ Centrality: mode, median, mean
■ The type of variable defines the centrality measure that we can use




■ Mean for the dichotomous variable equals proportion
● The proportion is basically the same as the percentage
○ Dispersion: Standard deviation
■ The sum of all squared distances to the mean.
● If all observations are clustered around the mean, the sum of
distances will be small.
● If observations are widely dispersed around the mean, the
sum of distances will be larger.
■ It’s a summary measure of the average distance to the mean.
■ If there is more dispersion, the standard deviations will be higher.

, ➢ Comparing distributions - z-scores
○ z-score: number of standard deviations from the mean




○ z-scores take into account differences in both centrality and dispersion
○ z-scores are a key concept in inferential statistics
○ z-scores help us to describe bell-shaped distributions
■ normal distributions - bell-shaped and symmetrical

Distributions of data




➢ Bell-shaped distributions (perfectly symmetrical around the mean ӯ)
○ we can describe it with empirical rule
○ 68% of all observation within 1 standard deviation from mean (between ӯ-sand ӯ+s)
○ 95,4% of all observations is between 2 standard deviations from mean (between
ӯ-2s and ӯ+2s)
○ 99,7% within 3 standard deviations (between ӯ-3s and ӯ+3s)
➢ we can apply empirical rule to all normal distributions
➢ frequency distributions
○ a listing of possible values for a variable, together with the number of
observations at each value

Probabilities and probability distributions

We can think of frequency distributions as probability distributions as well.
➢ provide probabilities for all the possible outcomes of a variable, lists the possible
outcomes and their probabilities
➢ I pick one random respondent that was sampled:

, ○ What is the probability that he/she/them is older than 20?
○ What is the probability that he/she/them studies more than 20 hours?
➢ We can determine this on the basis of the distribution!
➢ Probability = p
○ The probability is the area under the curve.
○ Each area under a bell-shaped curve can be expressed in a probability p

Standard normal distribution

➢ theoretical distribution used in inferential statistics
○ we use the standard normal distribution for calculations
○ bell-shaped and perfectly symmetrical
○ mean (ӯ) = 0, standard deviation (s) = 1
○ we can apply empirical rule here, too

➢ Probabilities can be defined as z-scores
■ in the standard normal distribution z = yi
➢ Every position in a normal distribution has a z-score with a corresponding probability.
○ Can be found in Table A.
○ For normally distributed variables we can convert z-scores to probabilities
(and the other way around)




Example using the table A

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 juliaradzieta. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $6.09. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

66184 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 15 years now

Start selling
$6.09
  • (0)
Add to cart
Added