New User Special Price Expires in

Let's log you in.

Sign in with Facebook


Don't have a StudySoup account? Create one here!


Create a StudySoup account

Be part of our community, it's free to join!

Sign up with Facebook


Create your account
By creating an account you agree to StudySoup's terms and conditions and privacy policy

Already have a StudySoup account? Login here

Psych 2220 review of ch. 9, and what to know for 10 and 11

by: MadsSwart

Psych 2220 review of ch. 9, and what to know for 10 and 11 Psych 2220

Marketplace > Ohio State University > Psych 2220 > Psych 2220 review of ch 9 and what to know for 10 and 11
GPA 3.54

Preview These Notes for FREE

Get a free preview of these Notes, just enter your email below.

Unlock Preview
Unlock Preview

Preview these materials now for free

Why put in your email? Get access to more of this material and other relevant free materials for your school

View Preview

About this Document

one sample t tests practice z statistics for a sample t statistics for one sample t statistics for paired sample one sample vs. paired sample t t statistics for paired samples t statistics f...
Data Analysis in Psychology
Joseph Roberts
Class Notes
psych 2220, Data Analysis, t tests, practice, z statistics, one sample, paired sample, t statistics, Statistics, z statistic, t statistic, independent samples, confidence intervals, Psychology, neuroscience, OSU, ohio state, effect sized, cohens d, d hat
25 ?




Popular in Data Analysis in Psychology

Popular in Department

This 4 page Class Notes was uploaded by MadsSwart on Sunday March 6, 2016. The Class Notes belongs to Psych 2220 at Ohio State University taught by Joseph Roberts in Winter 2016. Since its upload, it has received 16 views.


Reviews for Psych 2220 review of ch. 9, and what to know for 10 and 11


Report this Material


What is Karma?


Karma is the currency of StudySoup.

You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!

Date Created: 03/06/16
One Sample t-tests Practice Problems [worked out] 1. Mean = 2.81 SD=1.61 N=16 a. What z score would correspond to an observed value of 5? z=x−μ z= 5−2.81=1.36 b. σ  1.61 c. This was just a sample drawn from a population with µ=3 and σ=1.5 i. Mean; M=2.81 SD; s=1.61 N=16 ii. How likely is it to draw a sample N=16 whos mean is as extreme as 2.81? M−μ M M−μ M M=¿ = 2.81−3 σ M σ 1.5 1. √N = = -.51; Z √16 ¿ p=.61 iii. Calculate a one-sample t statistic for this sample, compared to a hypothesized population mean of 3. What do we conclude? 2.81−3 t( ) = 1.61 iv. = -.47; p=.65 √16 1. Table B-2: Critical Values in t distributions t(15) = -.4715 is the df (df=N-1) 2. Decision about the Null 1. We fail to reject H that µ=3 0 v. What values could we confidently identify as possible population means for the average approval level? Mupper samplcritM) 1. 95% confidence level M =M −t ∗ s lower samplcritM) 1. 2.81 = (2.132 x (1.61/√16)) =3.66 2. 2.81 – (2.132 x (1.61/√16)) =1.96 i. {1.96,3.66} 2. Mean 1: M=2.25 SD: s=1.44 N =16 Mean 2: M=281 SD: s=1.61 N 116 Difference: M=.56 SD: s=1.03 N D16 Taking these difference scores as a set of values, can we formulate and test hypotheses about the change in approval over time H 1 mean difference does not equal zero H 0 mean difference equals zero; zero difference 0.56−0 difference=¿ 1.03 √16 =2.18 t¿ - One sample t statistic computed for difference scores is fully equivalent to a paired-samples t statistic computed on the original pre- and post- scores. REVIEW OF CONCEPTS 1. Z statistics for a sample a. Z statistic can also refer to the mean x value for a sample of size N b. It represents a single observed mean in terms of its distance from the center of the sampling distribution of the mean – in terms of the population standard deviation σ i. Use σ to compute σ M 2. t statistics for one sample a. Converted version of a regular observed value for a sample mean b. Represents a single observed mean in terms of its distance from the center of the sampling distribution of the mean, as estimated by the observed sample standard deviation s. i. We use s to compute s w 3. t statistics for paired samples a. converted version of a regular observed z statistic for a sample mean b. it can also represent a single observed mean difference between two related observations, in terms of that difference’s distance from the center of the sampling distribution of the mean difference, as estimated by the observed sample difference standard deviation s D i. we use s to compute s D mean_difference 4. one sample t vs. paired samples t a. one sample t i. it represents a single observed mean in terms of its distance from the center of the sampling distribution of the mean, as estimated by the observed sample standard deviation, s. b. paired sample t i. represents a single observed mean difference between two related observations, in terms of its distance from the center of the sampling distribution of sample standard deviation of differencesDs 5. t statistics for paired samples a. This is all pretty much what we need to know for chapter 10 b. when and how to compute the difference between related observations c. set that group of difference scores as your one sample of scores for a one-sample t test d. exception: effect size estimates for paired samples are not always so directly analogous to the one-sample approach 6. t statistics for independent samples a. unrelated samples or non-paired samples b. one sample t test compares an observed sample mean to a population mean c. independent samples t test compares an observed sample mean to another observed sample mean (M and M ) A B i. there are complexities in estimating variability for this situation d. if the samples are actually independent, then the scores vary independently of each other i. need to add the two samples’ variances together within the t-statistic formula we’ve been using ii. exactly how we do that is just a matter of implementation 1. and there’s chapter 11 7. confidence intervals for t tests a. σM  s M critical z  critical t b. Confidence intervals for the mean i. When hypothesis-testing, we’re asking whether a sample mean deviates from a true population mean. Implicitly, we’re trying to estimate the true population mean 1. Our sample mean M is a point estimate of µ 2. We can build an interval around M that describes a range of values that we are confident will include µ a.Use t criticald solve for µ upperand µ lower b.Z criticaltcritical 8. Effect sizes a. Should we care about this observed difference from the population mean? i. It is important in the sense of a big effect? ii. Big effects might still not be significant. Recall similar distinction between strong vs. significant correlations b. Extent of difference between means (observed mean and population mean) i. Alt: the extent to which participants’ mean exceeded the value expected by chance (H 0 c. Estimated effect size i. Already calculated effect size scaled directly to sigma ii. Now scale to our estimate of sigma – estimated by s iii. We call the first equation, d-hat 1. But just refer to it as cohen’s d (M−μ) d= σ (M−μ) d= σ


Buy Material

Are you sure you want to buy this material for

25 Karma

Buy Material

BOOM! Enjoy Your Free Notes!

We've added these Notes to your profile, click here to view them now.


You're already Subscribed!

Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'

Why people love StudySoup

Bentley McCaw University of Florida

"I was shooting for a perfect 4.0 GPA this semester. Having StudySoup as a study aid was critical to helping me achieve my goal...and I nailed it!"

Anthony Lee UC Santa Barbara

"I bought an awesome study guide, which helped me get an A in my Math 34B class this quarter!"

Jim McGreen Ohio University

"Knowing I can count on the Elite Notetaker in my class allows me to focus on what the professor is saying instead of just scribbling notes the whole time and falling behind."


"Their 'Elite Notetakers' are making over $1,200/month in sales by creating high quality content that helps their classmates in a time of need."

Become an Elite Notetaker and start selling your notes online!

Refund Policy


All subscriptions to StudySoup are paid in full at the time of subscribing. To change your credit card information or to cancel your subscription, go to "Edit Settings". All credit card information will be available there. If you should decide to cancel your subscription, it will continue to be valid until the next payment period, as all payments for the current period were made in advance. For special circumstances, please email


StudySoup has more than 1 million course-specific study resources to help students study smarter. If you’re having trouble finding what you’re looking for, our customer support team can help you find what you need! Feel free to contact them here:

Recurring Subscriptions: If you have canceled your recurring subscription on the day of renewal and have not downloaded any documents, you may request a refund by submitting an email to

Satisfaction Guarantee: If you’re not satisfied with your subscription, you can contact us for further help. Contact must be made within 3 business days of your subscription purchase and your refund request will be subject for review.

Please Note: Refunds can never be provided more than 30 days after the initial purchase date regardless of your activity on the site.