Psyc 3101, Homework 4
Your 3-year-old niece has a vocabulary of 500 words, which gives her a z-score of +1 for kids her age. Your neighbors
kid has a vocabulary of 200 words and a z-score of -2.
1. Whats the standard deviation?
The z-scores differ by 3, m
Psyc 3101, Homework 3
This density plot shows a Uniform distribution.
All scores between 0 and 1 are equally likely.
1. What proportion of scores area greater than .8?
These scores correspond to the area under the curve
between .8 and 1.0 on the x axis. T
Psyc 3101, Homework 5
Due Oct. 2
We know the sample mean is our best estimate of the population mean, but how good is it? How much can we rely on
the sample mean to be close to the population mean? These exercises will give you an idea of how we answer th
Psyc 3101, Homework 12
Imagine you grew up in a family with five children. Every night, your parents choose a different kid to set the
table for dinner. You wonder whether theyre being fair, so over five weeks you keep track of how many times
each of you
Psyc 3101, Homework 9
Due Nov. 6
Name:
TA:
Daniel
Dorian
Jess
Kiri
Nicole
Imagine we have measured 8 subjects on two variables, X and Y. The data are below. You want to
figure out how X and Y are related to each other. Youll do this first by calculating t
Psyc 3101, Homework 11
Semantic priming involves presenting a word very briefly (e.g., for 20 ms) before presenting another word that
the subject has to identify. The prime word (i.e., the first word) can be identical to the target word (the second
word),
Psyc 3101, Homework 1
Due Sept. 4
Name:
TA:
Lab Time:
These problems are to help you judge your preparation for this course. Your answers will not be graded.
You will receive 100% on this assignment as long as you turn it in. Do NOT use a calculator.
1. 6
Psyc 3101, Homework 8
Due Oct. 23
Name:
TA:
Daniel
Dorian
Jess
Kiri
Nicole
Imagine you run an experiment testing the effect of weather on peoples mood. You administer the PANAS
(Positive and Negative Affect Scale) to one group of subjects on a rainy day a
Psyc 3101, Homework 7
The bus schedule says your trip to school should take 10 minutes. Sometimes it takes a bit longer, sometimes
a bit less, but you wonder whether on average its longer than what the schedule indicates. You time your ride
every day for
Psyc 3101, Homework 6
The deer in Chautauqua spend each morning in one of three groves, but there doesnt seem to be any pattern
to where theyll be each day. When I take my dog out in the morning, he races into the trees, hoping to find
deer. I wonder whet
R version 2.15.1 (2012-06-22) - "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i386-apple-darwin9.8.0/i386 (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welco
Notation and Equations for Exam 1
X: The variable we measure in a scientific study
n: The size of the sample
N: The size of the population
M: The mean of the sample
: The mean of the population (Greek letter mu)
x: Any possible value of the measurement va
Summary of Lab Week 1
Sept 4-10
Basic calculator
Addition:
> 7+4
Subtraction:
> 7-4
Multiplication:
> 7*4
Division:
> 7/4
Exponents:
> 7^4
Modular arithmetic (remainders):
> 7%4
Variables
A variable is a name you create that stands for some number or set
Summary of Lab Week 10
Nov. 6 12
Regression
Regression tells us how one variable or set of variables predicts another. We
call the variables that do the predicting the predictors, and we call the variable
being predicted the outcome.
Load the data in lab1
Summary of Lab Week 9
Oct. 30 Nov. 5
Correlation
Load the data in lab9-1.txt on the course website. This dataset contains two
variables, X and Y, that were measured for a single set of subjects. The fact
that theyre from the same set of subjects means X[1
Summary of Lab Week 11
Nov. 13-19
ANOVA
A simple ANOVA allows us to test whether any number of groups have reliably
different means. Start by loading the example data in lab11-1.txt on the
course website. Run a summary of the data to see what the variable
Summary of Lab Week 7
Oct. 16-22
t-test
First, we'll walk through the steps of a single-sample t-test. Make up a sample
with 5-10 data.
> X = c(_,_,)
Look at your sample and come up with a reasonable number for the population
mean under the null hypothesi
Summary of Lab Week 8
Oct. 23 - 29
Paired-samples t-test
Create two paired samples, X.A and X.B. The fact that theyre paired means
X.A[1] goes with X.B[1] (e.g., these are two measurements from the same
subject), etc. We will do a paired-samples t-test to
Summary of Lab Week 5
Oct. 2 8
Loops
Sometimes we want to repeat essentially the same command several times. We do this using
what programmers call a loop. R does loops with the for() command. Try this:
> for(i in 1:5) print(i)
This command tells R to rep
Summary of Lab Week 6
Oct. 9-15
Sampling distributions
Let's work through how to construct a sampling distribution. We'll use the distribution of sample
means as an example, starting with a case where the population is Normally distributed. Recall
that th
Summary of Lab Week 2
Sept. 11-17
Data frames
If you have a set of measurements on the same set of subjects, it's useful to organize them into a single structure
called a data frame. A data frame is like a matrix, meaning it has rows and columns. Each col
Summary of Lab Week 3
Sept. 18-24
Descriptive statistics
Mean, median, variance, and standard deviation all have built-in functions:
> mean(X)
> median(X)
> var(X)
> sd(X)
You can also get standard deviation using var(X) and the sqrt() function, which doe
Summary of Lab Week 4
Sept. 25 Oct. 1
Random numbers
R has built-in functions that will generate random numbers. You can think of these numbers as
samples from a mathematically ideal population. For example, the rnorm() function samples
from a perfect Sta
Psyc 3101, Homework 2
Due Sept. 11
Write whether each of the following is an experiment (yes or no). 1 point each
1. Monkeys with and without their prefrontal lobes removed are compared on a working memory task.
Yes. Removing the prefrontal lobes is a man
Notation and Equations for Regression Lecture
11/6
Notation:
m: The number of predictor variables in a regression
Xi: One of multiple predictor variables. The subscript i represents any number from 1
through m
Notation and Equations for ANOVA Lecture
11/8
Notation:
k: The number of groups; the number of levels of the independent variable in an ANOVA
Mi: The sample mean of Group i. The subscript i represents any n
Related or Paired Samples t test versus
Independent Samples t test
Bo th a s ks a m e q ue s tio n :Are th e m e a ns o ftwo
g ro up s o fs c o re s d iffe re n tfro m e a c h o th e r.
Ind e p e n d e nta s s um e s no LINK S(Nowaytomatch
particularsc