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

Psy 202 Exam 1 Study Guide

by: Anna Ballard

Psy 202 Exam 1 Study Guide Psy 202

Marketplace > University of Mississippi > Psychology > Psy 202 > Psy 202 Exam 1 Study Guide
Anna Ballard
GPA 3.33

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

This is a brief overview of some things I found important for this first test (Ch. 1-5).
Elementary Statistics
Mervin R Matthew
Study Guide
Psychology, Statistics
50 ?




Popular in Elementary Statistics

Popular in Psychology

This 6 page Study Guide was uploaded by Anna Ballard on Monday September 12, 2016. The Study Guide belongs to Psy 202 at University of Mississippi taught by Mervin R Matthew in Fall 2016. Since its upload, it has received 30 views. For similar materials see Elementary Statistics in Psychology at University of Mississippi.


Reviews for Psy 202 Exam 1 Study Guide


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: 09/12/16
Fall 2016 PSY 202 Section 4 Exam 1 Study Guide Chapter 1 • Experiments V. Quasi experiments v. observational designs - RESEARCH o Experiments – random assignment, takes people by random and groups them  Helps determine cause and effect  Too much control –> reduces external validity instead of increasing it o Quasi-Experiments – NOT RANDOM  Can see some cause and effect  More external validity with decreased control o Observational Studies  Does NOT tell cause and effect  All external validity  All observations of outside world – experimenter has NO CONTROL • Populations v. Samples - Population – dealing with the whole population o GREEK LETTERS - Sample – subset of population o English letters - Definitions o Get data points from different sources;  Whole picture –> population size  Test a sample of population to generalize back to that population  Sample MUST represent a population - Population Parameter –> Greek letters - Sample Statics –> English letters • Representatives - Sampling techniques – simple random, stratified, cluster, systematic, deliberate/purposive, convenience o Simple random – most preferred way because everyone gets equal chance to be chosen  May not get same representation between sample and population o Stratified sampling – gives same percentage between the two  Better for smaller groups o Cluster sampling – subgroups in a sample –> pull some from that group –> get sample o Systematic sampling – not everyone has an equal chance because every ____th person will be chosen  No representation of population  A little biased o Deliberate/purpose sampling – sample that compares with another sample; specific population o Convenience sampling – easiest data to collect but harder to generalize to the population  Mostly used in college settings • Variables - Independent V. Dependent o Independent (IV) –> does not change; dependent variable relies on independent o Dependent (DV) –> variable that depends on other factors (including IV)  Manipulated variable - Qualitative V. Quantitative o Qualitative –> categorical; no fractions; discrete o Quantitative –> numerical; fractioned; continuous - Continuous V. Discrete • Measurement Scales - Nominal – only categorical - Ordinal – categorical and ranking information - Interval – distance, rank, and categorical; zero is just a point of reference - Ratio – rank, categorical, distance, and true zero o True zero – absence of something • Reliability (in general) - General results of an experiment or study - Higher reliability means results are consistent - Lower reliability means inconsistent results - Reliability can give us a clear prediction o Cannot have validity without reliability • Validity (in general) - Measure what you think you are measuring to make a valid conclusion - Ensure validity comes down to operational definitions - Control any variable that may change alongside the IV Chapter 2 • Quantitative Data – Frequency Tables –> organize in descending order and count each group - Simple frequency – shows number of times a piece of data shows up o Include all possible values between high and low (use 0 for values not in table) - Relative frequency – how much is “a lot”? o Must be relative to something o round to 2 decimals o sums to 1.00 o round to 3 when multiplying and dividing - Cumulative frequency – Start with “n” and subtract f(y) as you descend o simple frequency and grouped cumulative should match up at the end o should end with last f(y) - Group Frequency Distributions o Grouping values –> used when there is a large range of data o Groups we are dealing with (intervals)  How many intervals  How wide should the intervals be? AKA how many values o How many intervals should we have?  Between 10 and 20, depending on distance between low and high value o How wide should our intervals be?  2, 3, 5, or a multiple of 5, depending on the number of values used and subsequently, intervals. • Histograms, frequency polygons, ogives, and stem-and-leaf plots - Histograms – simple and relative frequencies o Great graph when there is a lot of data o X-axis –> values of raw scores  Values of raw scores in ascending order (either grouped or ungrouped) o Y-axis –> frequencies o Vertical bar for each group (AND TOUCHING)  Compares scores for us - Frequency Polygons – similar to histograms o X-axis: still values from lowest to highest o Point for each f(y) value o Connected points suggest values for scores on a continuum  Points just outside of range touch the X-axis - Ogives o X-axis still o Y-axis –> cumulative frequencies (simple or relative)  Highest cumulative frequency always = 1.00 (relative) or n (simple)  Points not necessarily connected by lines - Stem-and-Leaf plot o Get shape and scores only o individual scores o intervals divide evenly into 10 o All group Chapter 3 • Measures of Central Tendency Mode – which score that has highest relative frequency 0 2 2 2 3 4 4 5 7 8 9 - Our class does not like mode because it could be far away from the central tendency - There can also be more than one mode - Mode does not consider anything else in a distribution - Only use mode when you absolutely have to because it only gives us info on category membership - Applies to all data Median – score that has 50% distribution below and above 0 2 2 2 3 4 4 5 7 8 9 - If 2 different scores straddle median… average the 2 - We like this more than mode because it tells us about rank - Missing info: does not give us distance between scores - Better when there are outliers Mean – preferred because it includes the most information (category, rank, and distance) - Incorporates how much the scores weigh - The average of all the scores - CREATES A BALANCE POINT - Most sensitive to outliers n µ = ∑ Yi/n µ –> populi = 1 mean i = 1 –> start with this score n (above ∑) –> finish with this score Y –>raw score; sum all of these scores –> inclusive • Variability More variability –> less confident - Range – Everything between highest score and lowest score (subtract low from high) o super duper sensitive to outliers - Interquartile Range – better to use to “cut off” outliers • Average Deviation vs. variance and Standard Deviation - Average deviation – absolute value bars prevent cancelling out - Variance – squared average deviation also prevents cancelling out - Standard deviation – square root allows data to be closer to original units o Definitional formulas rely on the mean – can get rounding errors and make those rounding errors worse by squaring • Degrees of Freedom – number of categories minus 1 (n-1) - For every parameter we estimate, we lose one degree of freedom Skewness and Kurtosis • Skewness – measure of distribution - Negative distribution – mean closer to negative value - Positive distribution – mean closer to positive value • Kurtosis – measure of curvature - Assumes 0 - Negative distribution is flat compared to positive with high arch Box and Whisker Plots - give us measure of central tendency and measure of variance o measures and medium; lower and higher; range - allows us to see distance Chapter 4 • Frequency tables – Almost always going to be ungrouped - Order does not matter - no cf(Y) because you cannot have scores that are below a certain level • Bar Graph – scores are discrete (bars do not touch) - when dealing with categorical scores there is no skewness or kurtosis • Pie Chart – harder to read visually - good to use when dealing with budget - slices can be in any order ** both pie chart and bar charts are histograms because they only show relative frequency and percentage *** Chapter 5 Expressing the Ordinal Position of a Score • Percentile and percentile rank –> give ordinal only * Percentile Rank : raw scores –> cumulative relative frequency - used more often because of an easier conversion • Percentile : cumulative relative frequency –> raw scores *** Cumulative relative frequency (CRF) is always written in decimal form *** - use that to figure out % at or below your level - CRF = 0.63 –> 63 percentile rank - Always round down to chop off extra decimal places (AKA no fractions @ percentiles) Interpreting Percentile Rank - Can tell you if someone is above or below someone else but not by how much - Aka no distance info! Setting Standard: Normal distribution - How many standard deviations is it above/below mean? - These are standardized (z) scores o Mean always = 0 in distribution scores o Standard deviation always = 1 o (+) –> high magnitude o (-) –> low magnitude


Buy Material

Are you sure you want to buy this material for

50 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

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."

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."

Parker Thompson 500 Startups

"It's a great way for students to improve their educational experience and it seemed like a product that everybody wants, so all the people participating are winning."

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.