12/02_MEETING

Question 1

TRUE OR FALSE: The typical recommendation for effect size is small-to-large.

Answer 1

TRUE.

Question 2

TRUE OR FALSE: Power level would say “I detected light correctly” while Type I would say “I detected that this was incorrect”

Answer 2

TRUE.

Question 3

TRUE OR FALSE: The higher value the better for your Type I error rate.

Answer 3

FALSE.

The lower.

Question 4

TRUE OR FALSE: To detect sample size, you need the three variables of error rate, Type 1 error and power level.

Answer 4

TRUE.

Question 5

TRUE OR FALSE: You cannot compute for prospective power analysis in R.

Answer 5

FALSE.

You totally can. There’s a syntax and you need the pwr library.

For linear regression, pwr.fw.test 
u=1 because simple linear regression
sig. level = .01 (error rate) 
f2 = .02 (small to large) 
power = 0.80 (small to large) 

Get the v (those are your participants)

For you to have this scenario, you need 585 (minimum) participants in your sample

Question 6

TRUE OR FALSE: .02, .15, .35 is Cohen’s f2 for small-to-large, medium-to-large, and large, respectively

Answer 6

TRUE

Question 7

Why does Sir Sagmit tell his students to plus minus 50 to 100 students?

Answer 7

Because you anticipate that you will lose participants (you might need to do outlier chuchu)

Question 8

What does prospective power analysis serve?

Answer 8

To get sample size.

Question 9

TRUE OR FALSE: When you conceive research that yields a linear regression, it is recommended that you use prospective power analysis to get sample size.

Answer 9

TRUE.

Bawal hula.

Question 10

How do you conceive a simple linear regression?

Answer 10

Identify a predictor and an outcome from the variables in the file provided for.

Question 11

How do you conceive a simple linear regression?

Answer 11

Identify a predictor and an outcome from the variables in the file provided for.

Question 12

What is the generic question in simple linear regression?

Answer 12

Does the predictor predict the outcome? (Does dad indifference predict high standards for self?)

Question 13

Which software does Sir Sagmit use to get linear regression?

Answer 13

JASP (not R, this time)

He doesn’t recommend bootlegging SPSS—best alternative is still R, but if you want the point and clic, JASP is one and JAMOVI is another one (fun fact: JASP and JAMOVI evolved from R)

Question 14

What are the two types of regression JASP provides in its options?

Answer 14

Classical (frequentist)— Sir doesnt subscribe to this, but “unfortunately” we still need to learn this

Bayesian—“the future is Bayesian” but unfortunately no one is teaching Bayesian; Bayesian isn’t new, it’s from the 1960s but they didnt take it up; this has “complexity” and harder????

Question 15

[SIR SHOWING RESULTS IN LINEAR REGRESSION THRU JASP?]

What does R^2 tell you

Answer 15

How much of the variable is being predicted by the equation of the line, or the statistical model?

R^2 = 0.004 (only 0.4% of your variable was being explained by your equation of the line)

Question 16

What are the three parts of your linear regression results in JASP?

Answer 16

Model Summary - HIGHSTANDARDS
ANOVA
COEFFICIENTS

Question 17

Under ANOVA, what does the p indicate?

Answer 17

“Imagine a world where anything that you say was simply due to chance. Nagkataon lang. So there’s nothing definite. So that means, it’s not statistically significant.

Now you observed 0.4% (this was predicted by the equation of the line), so how often will you find this in a world where predictions are random?

There’s a 46% probability that the predictions you actually observed that the predictions will be observed in a world where all predictions are random. In other words, your predictions might be simply random. (So it’s statistically non-significant)

Just think of it in the world where everything is chance.

Question 18

When do we use y-intercepts?

Answer 18

When we try to look for predictions?

Question 19

What does DADINDIFFERENCE of 0.053 (under understandardized in coefficients) mean or imply?

Answer 19

For every 1 unit increase in DADINDIFFERENCE, you predict a 0.053 increase in the other variable.

BUT YOU DONT WRITE IT THAT WAY IN YOUR REPORT. (refer to 9.09)

“When you see dat beta coefficient you know what’s going on”

Question 20

Is the former statistically significant?

Answer 20

Check the p in the table.

It should be less than 0.05. (In this case, it’s not.)

Question 21

[SIR SAID TO LOOK AT HIS FILE ABOUT EXPLAINING)

Answer 21

[Ysa, input what it looks like and apply the analysis is here.]

The beta coefficient is 0.3, for every one unit increase… there’s a 0.3 increase in the other one. (Review this pls)

Question 22

[Johanna asked about covariance table and Sir is addressing it]

Answer 22

You know cor = cov/(SDxSD)

Question 23

Where do you find the equation of the line?

Answer 23

Look at the coefficients table, and look at the variables

Question 24

TRUE OR FALSE: It is possible for one variable to be statistically significant and another to be statistically insignificant.

Answer 24

TRUE.

*

Question 25

How does COPEACCEPT predict?

Answer 25

After controlling for COPEACCEPTANCE, for every 1 unit increase in MOMINDIFFERENCE, you expect a 0.47 increase

“After controlling for” is important. There is a difference between statements that have this and do not have this

Question 26

TRUE OR FALSE: The formula is always empirical divided by theoretical.

Answer 26

TRUE.

Question 27

TRUE OR FALSE: The Blasians like dichotomous thinking.

Answer 27

FALSE. They hate it.

Question 28

TRUE OR FALSE: Effect sizes became very popular due to estimation thinking.

Answer 28

TRUE.

Question 29

TRUE OR FALSE: Estimation thinking is being debunked and now we have meta-analytic thinking.

Answer 29

TRUE.

Question 30

“When you divide the world into two, you’re losing the fifty shades of gray.” (Estimation thinking)

Answer 30

TRUE.

Question 31

TRUE OR FALSE: Our science (psychology) is probabilistic.

Answer 31

TRUE.

Dichotomous thinking is actually a violation to the nature of psychology, because nothing is absolute. (Shouldn’t we be dealing with estimates—what is the probability?)

Question 32

What is the probability of an event under the given condition?

Answer 32

Conditional probability

Event is empirical, condition is theoretical, or what is ideal

Question 33

TRUE OR FALSE: The p-value is a conditional probability.

Answer 33

TRUE.

The condition is the null hypothesis (nagkataon lang)

Probability of an event under a certain condition

Question 34

TRUE OR FALSE: All our science is based on frequentist or statistical inference.

Answer 34

TRUE.

Question 35

What is the dfiference between frequentists and bayesians when it comes to probability?

Answer 35

F - P (data/theory)

B - P(theory/data)

Question 36

TRUE OR FALSE: We are putting the theory in the gold standard (or the hypothesis) when we look at the frequentist view.

Answer 36

TRUE.

Question 37

Which view of probability leaves more for probability?

Answer 37

Bayesians view

Question 38

r means relationship

Answer 38

yea

sana ol

Question 39

Which view goes “IN THE LONG RRRRRRUN, you will observe in a world with no correlations, you’ll observe this 6 times”

Answer 39

Frequentist view

Question 40

DID YOU KNOW THERE ARE 3 TYPES OF HYPOTHESIS TESTING

Answer 40

yessir yessir 3 bags full

Question 41

What are the 3 types of hypothesis testing?

Answer 41

Test of statistical significance
Test of acceptance
Null hypothesis significance testing (NHST)

Question 42

TRUE OR FALSE: Sir hopes you use NHST

Answer 42

False.

Question 43

Hypothesis testing?

Answer 43

Estimate the strnegth of evidence against null hypothesis; which of the two competing hypothesis is more likely to reflect your data

Question 44

Why does Sir not like NHST?

Answer 44

DECISIONS KASI and this is weird for psychology; it’s flawed! what would be the best alternative? some would say the baysians. but problem? no one’s teaching it. some say likelihood would be better (AIC-based procedures), however in the spirit of really understanding the nature of hypothesis testing (what i do in the undergrad) is to go back to the roots (aka test of statistical significance and test of acceptance)

Question 45

What are the two types of hypotheses in the test of acceptance?

Answer 45

Main hypothesis and alternative hypothesis