BASIC CONCEPTS Flashcards

1
Q

METHODS OF GETTING AT THE TRUTH - What is the use of authority?

A

Something is considered true because of tradition (has power of someone/something in a position of power) or because some person
of distinction says its true.

ex: white coat

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2
Q

METHODS OF GETTING AT THE TRUTH - What is the use of rationalism?

A

The use of reasoning alone to arrive at knowledge.

ex: logic, premisses

A blue jay is a bird.
All birds have wings.
Therefore, a blue jay has wings.

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3
Q

METHODS OF GETTING AT THE TRUTH - What is the use of intuition?

A

Sudden realization or insight that seems to emerge out of nowhere, without conscious reasoning. It’s like a “light bulb moment” where everything clicks into place all at once, offering clarity or an answer. It often seems to occur after conscious reasoning has failed (knowing the answer of a question after giving back the exam).

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4
Q

METHODS OF GETTING AT THE TRUTH - What is the scientific (research process) method of getting at the truth?

A

This method involves using both reasoning and intuition to arrive at a potential truth, but then critically and objectively assessing the results to determine if they are valid:

1) Observations made, presence of a research question, measurements planned, a logical
strategy for answering the question is selected (method), and data collected

2) Data are analyzed statistically, and decisions are made concerning the answer to the question

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5
Q

METHODS OF GETTING AT THE TRUTH - What does it mean to analyze statistically data?

A

It allows the numbers to talk instead of “what we tend to believe”.

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6
Q

What does “population” mean in research?

A

The complete set of individuals, objects, or scores that the researcher is interested in studying. In an actual experiment, the population is the larger group of individuals from which the experimental subjects have been taken.Basically the “big picture” of your sample.

e.g. : let’s say you conduct a study on the average height of women in Canada. Ideally, you would study every single woman in Canada (the population). Since it’s impossible to do so, you will have a sample instead.

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7
Q

What is a sample?

A

A subset of the population from which the experimental data is collected. ** try to make it as représentatif possible of your population studied **

example: one spaghetti noodle in the whole pot boiling

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8
Q

What is a variable

A

Anything that is measured or manipulated in a study.

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9
Q

What is the relationship between the independent variable (IV) and the dependant variable (DV)?

A

Manipulate the IV, and measure the effects of this manipulation on the DV.

e.g. : How does drug X dosage (IV) affect blood pressure (DV)

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10
Q

What is data?

A

Measurements that are collected. Often referred to as raw/original scores. ** Raw because have yet to be analyzed/interpreted **

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11
Q

What is a statistic?

A

A number calculated on sample data. It quantifies a characteristic (probability, range, average…) of the sample.

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12
Q

What is a parameter?

A

A number calculated on population data. It quantifies a characteristic of the population.

**Since it’s usually impractical to collect data from an entire population, we take a statistic from a sample and then generalize it to estimate the corresponding parameter for the population.

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13
Q

From the following example, what would the IV, DV, sample, population, data, statistic, and parameter?

A real estate company is interested in testing whether the mean time that families in Gotham have been living in their current homes is less than families in Metropolis. The real estate company randomly selects 100 families from each city, and figures the average length of residence in current homes.

A

IV: cities

DV: length of residence in current homes

Sample: 200 families

Population: all the families living in Gotham and Metropolis

Data: length of residence in current home per family

Statistic: Average length of residence in current home for each group because it measures a characteristic of the sample score.

Parameter: none, because no measurement of the population was done

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14
Q

What is descriptive statistics?

A

Descriptive statistics are used to describe the obtained data. They do not go beyond the observed data. No sample cause no inferring to the population.

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15
Q

What are inferential statistics?
Give an example.

A

Inferential statistics use the obtained data to infer to populations. Basically, we draw conclusions that go beyond the observed data; we generalize from the sample to the population.
** key word: sample. As soon as you see it, it means we took a sample to represent a population! **

e.g.: What is the average IQ of Concordia students?
Randomly select the students and then generalize observed data.

Asking 1000 Americans who they are gonna vote for, then generalize to predict election results.

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16
Q

Is this an inferential or descriptive statistic? There have been 82 confirmed or suspected suicides among active-duty service personnel this year, compared to 51 for the same period in 2008.

A

Descriptive.

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17
Q

Is this an inferential or descriptive statistic? Survey results revealed that 26% of thirsty golfers order a sports drink when they finish their round and head for the clubhouse.

A

Inferential.

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18
Q

What is a continuous independent or dependent variable?

A

A continuous variable can assume an infinite number of values between any two points (e.g. weight, height, time…). C’est continu!!!

example:
IV = amount of sleep
DV = cognitive performance (by using test scores)

19
Q

What is a discrete independent or dependent variable?

A

A discrete variable can assume only a finite number of values between any two points (e.g. number of children). **Usually IVs are discrete

EXAMPLE:
Let’s say you’re studying the impact of parenting style on children’s behavior. In this case, parenting style could be your independent variable (IV), and it could be discrete because you might categorize it into different types, such as:

Authoritarian
Permissive
Authoritative
Neglectful

Here, parenting style is a discrete variable because you can only have specific, distinct categories, and each individual can belong to only one category.

20
Q

What are the real limits of a continuous variable?

A

The values that are above and below the recorded value by one-half of the smallest measuring unit of the scale. There is the lower real limit and the upper real limit.

Formula:

real limits =
(recorded value +/-
(smallest measuring unit/2))

21
Q

Find the real limits of 100,011 (what I measured).

A

100,0105 (lower) and 100,0115 (upper).

100,011 +/- 0,0005

22
Q

What is the first thing you should ask yourself when wondering what are the real limits of a continuous variable?

A

What is the smallest measuring unit of that number measured.

23
Q

What is a measurement scale?

A

A measurement scale refers to the way in which variables are quantified or categorized. It defines the type of data you’re working with.

24
Q

What are the two primary measurement scales?

A

Qualitative and quantitative.

25
What is the difference between qualitative and quantitative variables?
Quantitative variables have values that are numbers. Qualitative variables have values that are qualities or categories.
26
What are the two qualitative measurement scales?
Nominal and ordinal. Nominal: - categorical (e.g. sex, marital status...) - the one we use the most Ordinal: - it's rank / order (pain level 6 is greater than pain level 3) - there is a magnitude (e.g. pain rating, stages of cancer...) - no equal interval. The difference doesn't have the same meaning; the difference between pain level 4 and 5 and pain level 2 and 3 is not the same. - greater than and less than relationships. example - running competition: Gold > Silver > Bronze Between Gold and Silver 2 seconds, but between Silver and Bronze, 10 seconds.
27
What are the two quantitative measurement scales?
Interval and ratio. Interval: - equal intervals - Magnitude - origin is arbitrary (e.g. temperature, 0 Celsius doesn't mean absence of heat, and compared to Kelvins, you can't say twice as much or wtv...) -greater than and less than relationships. Proof: At 25°C, it’s 298.15 K At 50°C, it’s 323.15 K Ratio: - equal intervals - magnitude -greater than and less than relationships. - fixed origin (length, mass, reaction time...): * The only time you can say twice as so and so... *
28
What are we interested in measuring in psychology?
Physical (i.e. reaction time) and non-physical variables (i.e. mood)
29
What is a construct in psychology? Give some examples.
A construct is a variable that is not DIRECTLY (keyword) measurable. For example, intelligence, memory, anxiety, mood, depression, stress.
30
How do we measure a construct?
1. Operationally define specific variables used to measure this construct * An essential component of an operational definition is measurement (operational measure) 2. We create a tool (i.e. questionnaire) that allows us to operationally measure (assign numbers to) a variable we are interested in. * These numbers provide the raw data for our stats analysis Go see examples diapo (dictionary def of a construct vs. operational definition)
31
What is distinction between construct and variable?
Construct: This is the abstract idea or concept you're trying to study. It's something broad and not directly measurable, like stress, intelligence, or happiness. Variable: This is something measurable that you use to represent the construct. A variable is a specific aspect or indicator of the construct that can be measured. So, while the construct is the big idea (like stress), the variable is a specific way you decide to measure that idea. Construct: Stress Variable: Anxiety level, heart rate, or self-reported feelings of being overwhelmed
32
What two criteria should the operational measure meet in order to accurately represent the psychological construct?
1. Reliability: The operational measure has to be stable, peu importe le nombre de fois que telle personne est testée - should give same/similar result. 2. Validity: "Does that mood test really measure mood"
33
Is error evitable ?
No, no matter how reliable and valid the operational measure is. All measurement is subject to some measurement error.
34
What is the Classic Test Theory?
Obtained Score = “True Score” + Random Error Obtained Score: The score you actually measure (e.g., the score someone gets on a test). True Score: The "real" score that reflects a person's actual ability or characteristic, free from any measurement errors. Random Error: The unpredictable fluctuations that cause the obtained score to deviate from the true score (e.g., distractions, fatigue, or guesswork).
35
Give 2 reasons why samples are studies instead of populations.
1. Usually more practical (difficult to manage, costly...) 2. GOAL OF SCIENCE is to make generalizations about events beyond our reach. (in order to estimate the population parameter).
36
What is the general strategy in psychology?
study a group of individuals who are believed to be representative of the general population (or some particular population of interest). Trying to minimize systematic differences between sample and population.
37
METHODS OF SAMPLING - What is simple random selection?
The researcher obtains a complete list of all the members of the population and randomly selects some number of them to study. Examples: 1) telephone survey 2) putting all the names on slips of paper and drawing them from a hat
38
METHODS OF SAMPLING - What is convenience sampling?
Selecting whomever is available without any systematic plan. This is likely to result in a sampling bias (biased sample). examples: 1) surveying each person you run into on the street 2) selecting students who sit in the front row Let’s say you want to study the study habits of college students to understand how they prepare for exams. Instead of selecting a representative group of students from different universities, majors, and backgrounds, you decide to survey only your friends in your psychology class. These friends are easy to reach and accessible, so you choose them for your study.
39
Why is true random sampling rarely possible
In psychology research, achieving true random sampling—where every single member of the population has an equal chance of being selected—is often difficult or impossible (access issues...). However, they still try to aim for a representative sample.
40
Why sampling should be random?
Because parameter estimates are much more accurate is samples are representative of population. And for samples to be representative of populations, all members should have an equal chance of being selected.
41
What is sampling error?
Difference between the statistic computed from the sample and the parameter computed from the population.
42
How to minimize sampling error? Basically how does the parameter estimate gets more reliable. 2 reasons.
By making sure the sample is representative to the population. How? 1) big sample size 2) random sampling (everyone had an equal chance of being selected)
43
What is the difference between "N" and "n"?
N = # of scores in the population n = # of scores in the sample
44
What is "X" or "Y" and "Xi"?
"X" or "Y" stands for the variable measured. It's the "i"th score, where "i" can vary from 1 to N. Score 1, 2......