Chapter 1 - Intro - Flashcards
Descriptive Statistics
vs.
Inferential Statistics
- Organize, summarize, and communicate numerical information about a sample . Describes the sample! (ex: how many hours of sleep does this one group get?)
- Use samples to draw conclusions about a population (ex: based on that 1 group, how many hours of sleep does the population of Langara get?)
2 things about Inferential Stats that allow us to use these values?
- Develop a margin of error for a value ( ex: I am 95% certain that the average # of sleep is b/w 5.63 and 6.62)
- Make decisions about 2 or more values (‘hypothesis testing’) (ex: the average 1st yr student sleeps longer than your average 2nd yr student)
What exactly is Statistics though?
- A Methodology : a set of procedres and rules for reducing large masses of data to manageable proportions and for allowing us to draw conclusions from those data
- A Numerical Value : the result of arithmetic or algebraic manipulation applied to data
MUST know WHY I’m doing a certain test to find a value. HOW & WHY.
A reason why Statistics is used?
- Allows us to see patterns
- Allows us to see if differences exist between numbers
- Allows us to see if things are related
- All about probability
Make confidence statements in the face of uncertainty.
Sample vs. Population?
- Sample : a portion of the population (gather descriptive statistics. Then, infer parameters.)
- Population: a collection of subjects or events that share a common characteristic
The 4 variables that researchers use to quantify observations?
- NOMINAL - aka Categorical levels because they are in levels (‘best’ tv shows. Numbers are meaningless though)
- ORDINAL - number represents ranked order (top 10 books of 2022)
- RATIO - like an interval, with meaningful distances, but also has a true 0 point, with 0 being nothing. (Like 0 degrees kelvin)
- INTERVAL - numbers represent equal intervals (distances) between levels, but there is no true zero point. ‘Likert’ scales are also considered interval scales (the scales that are strongly disagree, somewhat disagree, neutral, etc)
CALLED THE SCALES OF MEASUREMENT
What is a variable?
any characteristic that can differ in some way, as in ‘a’ and ‘b’. also, variable vary meaning they can assume different values
Variable values can be quantifiable (numeric) or categorical ( ex: gender)
a + b = 12
2 ways that statisticians use to describe ‘scale’?
Discrete variable
vs.
Continuous variable?
- can only take on specific values, like whole numbers (how many kids do you have?)
- can take on a full range of values (with decimal numbers)
Difference b/w independent and dependent variable?
Does sleep impact academic performance? The independent variable (sleep) predicts the dependent variable (academic performance).
- Independent:
- dependent:
What are confounding (confounds) variables?
What is used to control these confounds?
Variables which could also account for the outcome (which were not controlled) We want to try for only 2 variables accounting for the outcome.
Control for these confounding variables by randomly assigning particiants.
Difference between reliability & validity?
How are they related?
What is an operational definition?
How is it used for dependent/independent variables?
Needs 2 things to be a good definition:
1. RELIABILITY - consistency of a measure (are the values close to each other? Like getting within 0.10 mL of the other values in a chemistry lab)
2. VALIDITY - refers to whether the operational definitions measures what it intends to measure (asking someone every few months if they are depressed, and they say it their depression varies with their ‘mood’. Well, this is valid, because it’s measuring what it’s supposed to be measuring!)
Something can be reliable but not valid! and vice versa. Both things to be present.
O = T + ME
Obtained score = ‘True’ (hypothetical) score + error in measurement
We get the O but we don’t know what’s on the right side of the equation.
Define, in a scientific way, the word experiment?
Experimental vs. Correlational research?
What is meant by between-groups research design
&
within-groups research design?
- Take participants from both groups (let’s say the 5hr sleep group and the 8hr sleep group) and test them. The word “between” means that you’re comparing different conditions between groups.
- Take participants from only the 5hr sleep group and test them. Then do the 8hr sleep group. The word “within” means you’re comparing different conditions within the same group.
Correct the wrong word:
In a study on exam prep, every participant had an equal chance of being assigned to study alone or with a group. This was a correlational study.
A psychologist was interested in studying the effects of the dependent variable of caffeine on hours of sleep, and she used a scale measure for sleep.
change dependent to INDEPENDENT
Correct the wrong word:
In a study on the effects of the confounding variable of noise level on the dependent variable of memory, researchers were concerned that the memory measure was not valid.
A researcher studied a population of 20 rats to determine whether changes in exposure to light would lead to changes in the dependent variable of amount of sleep.
What is meant by Data Ethics?
What is Open Science?
A set of principles related to all stages of working with data – research design, data collection, statistical analyses, interpretation of analyses & reporting of outcomes.
It is an approach to research that encourages collaboration, and includes the sharing of research methodology, data, and statistical analyses in ways that allow others to question and even to try to recreate findings
What is an example of unethical practices with researchers?
skewing the data to best fit what I want
What is HARKing and pre-registration?
Hypothesizing after the results ARE KNOWN (collect the data, develop the hypothesis, then test that hypothesis with that data – self serving data!)
Supposed to be: Develop Hypothesis –> Collect Data –> Test Hypothesis
Pre-register: scientists register their hypothesis so they remain accountable
Calculating Stats:
A researcher studies the number of hours 2500 Canadians exercise every week. Identify the sample and the population for this example.
Calculating Stats:
A bookstore employee asked 225 students to complete a customer satisfaction survey after these customers bought their books. The manager wanted to find ways to improve the customer experience. Identify the sample and population for this example.
Calculating Stats:
Over the course of 1 week, a grocery store randomly selected 100 customers to complete a survey about their favourite products. Identify the sample and population for this example.
Calculating Stats:
A researcher studies the average distance that 130 ppl living in urban areas in India walk each week.
1. Size of sample?
2. Population?
3. Is the ‘average’ a descriptive stat or an inferential stat (used to describe the 130 ppl)
4. How might you operationalize the average distance walked in 1 week as a scale measure?