×

### Let's log you in.

or

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

×

or

by: Michelle H.

29

1

5

# STAT 2000: Intro Statistics Week 1 (Aug. 11th-Aug.18th) STAT 2000

Marketplace > University of Georgia > Statistics > STAT 2000 > STAT 2000 Intro Statistics Week 1 Aug 11th Aug 18th
Michelle H.
UGA
GPA 4.0

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

×
Unlock Preview

Notes from the first week of Stat 2000 at the University of Georgia. These notes contain an overview of the lecture, summaries of in-class activities, and vocabulary found in the reading. Pleas...
COURSE
Intro Statistics
PROF.
Georgia Gilbert
TYPE
Bundle
PAGES
5
WORDS
CONCEPTS
Statistics, Stats, intro to statistics, stat
KARMA
75 ?

## Popular in Statistics

This 5 page Bundle was uploaded by Michelle H. on Wednesday August 17, 2016. The Bundle belongs to STAT 2000 at University of Georgia taught by Georgia Gilbert in Fall 2016. Since its upload, it has received 29 views. For similar materials see Intro Statistics in Statistics at University of Georgia.

×

## Reviews for STAT 2000: Intro Statistics Week 1 (Aug. 11th-Aug.18th)

×

×

### What is Karma?

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

Date Created: 08/17/16
Stat 2000: Elementary Statistics  Week One: Aug. 11th to 18th       Defining Statistics  Statistics consists of:  ● Formulating a research question  ● The collections of data  ● Describing data  ● Drawing conclusions or generalizations from data    Statistics​ is the science of learning from data.     The Statistical Method  3 main components to answering statistical questions:  ● Design  ○ How the data is obtained  ○ Valid inferences cannot be made without a good design   ● Description  ○ Summarizing the data obtained  ○ Helps to identify patterns in the data  ● Inference  ○ Making predictions or decisions based on the data    1.2: Population and Samples    The ​population​ is the sed off all individuals we are interested in studying.  A ​sample​ is the subject of the population for whom we have data.  Subjects​ are the individuals who make up the sample.    Population  Sample  Subjects  The entire voting  200 randomly  Each voter  public  selected  in the  voters  sample  Every MLB player  60 randomly  Each  selected  player in  players  the sample  All 159 counties in  40 randomly  Each  GA   selected  county in  counties  the sample    A ​parameter​ is a characteristic in the population which we wished we knew. This is usually  unknowable.   A ​statistic​ is a numerical value that summarizes the sample data.  Statistics serve as estimates for population parameters.     Example: SEC Teams  Parameter​: The average weight of all SEC football players.  Sample​: 75 randomly selected SEC football players. (​n=sample size​)  Population:A single player from the sample  Subject: All SEC football players  Statistic: The average weight of the 75 SEC players      Term  Symbol  Population mean (parameter)  μ (mu)  Sample mean (statistic)  x (x­bar)  Population proportion   p  (parameter)  Sample Proportion (statistic)  p̂  (P­hat)        Experimental and Observational Studies  Two basic ways to gather data:  ● Experiments  ○ Manipulating or influencing the subjects in order to obtain the data.  ○ Usually, subjects are assigned to a control group and a treatment group.  ○ Properly designed experiments can be used to prove causation.  ● Observational Study  ○ Measures the characteristics of the subjects without attempting to manipulate or  influence the subjects  ○ Cannot be used to prove causation, but can conclude that the two variables are  related.              Methods of Sampling  ● Simple Random Sampling  ○ Each subject in the population has the same chance of being included in the sample  ○ Ideal method of sampling, but not always possible  ■ Without replacement​: Subjects chosen are not returned to the population,  can’t be chosen again  ■ With replacement​: Possibility for a subject to be chosen multiple times in the  same study.  ○ Sampling Variability​: Since each sample contains different subjects, the data  retrieved from an experiment may vary from sample to sample.  ○ Statistically speaking, simple random sampling is considered the most sound  method.  ■ However, this does not guarantee that the sample is an accurate  representation   ● Stratified Sampling  ○ The population is divided into non­overlapping groups called ​strata​.  ○ A simple random sample is selected from each strata.  ■ Eg. From the student population, possible groups could include international  students, athletes, and all other students.  ○ Ensures that all minorities within the population are accurately represented  ○ Only applies if the distinction between members within a population could affect the  study.  ■ Eg. Whether or not a student is an athlete may affect a survey about the  average fitness level of students.  ● Cluster Sampling  ○ The population is divided into groups and all individuals within a randomly selected  groups are sampled  ○ Unlike satisfied sampling, the groups in this method are entirely arbitrary.  ● Convenience Sampling  ○ The sampling is made up of subjects that are easily obtained  ○ Generally, this is not the best method to make a statistically sound survey, may  contain bias  ■ Eg. Online surveys  ● Systematic Sampling  ○ A rule is used to select members of a sample  ■ Eg. Selecting every 10th member from the population  ○ Removes bias    Often, the method of sampling fits with what is logistically possible in regards to the survey.              Activity  ● Simple Random Sampling:  ○ Selected random people from class using a random number generator three times.  Sometimes, students were present in multiple groups of numbers  ● Stratified Sampling  ○ Students given cards with three different symbols and then divided into those groups.  ○ Students were randomly selected from these homogeneous (similar) groups  ● Cluster  ○ Randomly selected 3 out of 11 rows in hall, data was obtained from ​every​ student in  these rows.      Probings in Sampling  ● Sampling Bias  ○ Occurs when the samples are either non­randomized or from under coverage  ○ Under coverage​: Parts of the population that aren’t represented  ■ Eg. A phone survey omits those within the population who do not have  phones  ○ When this occurs in a study always practice ​transparency​, or alerting others of the  flaw in your sampling process  ● Response Bias  ○ Subjects give an incorrect response (or lies) or when the questions are asked to the  participants in confusing or misleading ways  ■ Eg. Wording a survey to lead responders to agree or disagree with the  statement  ● Nonresponse Bias  ○ Some sampled subjects cannot be reached or refuse to participate in the survey  ○ The subjects that are willing to participate often may have strong opinions about the  subject matter, making the survey not representative of the population  ■ Eg. If a survey is sent out to 500 households and only 20 households  complete it, those 20 do not accurately represent a “normal household"    Poor Ways to Study  ● Convenience samples​ typically do not represent the population  ● When respondents volunteer to participate, individuals with the strongest opinions on either  side of an issue are much more likely to respond  ○ This creates a ​voluntary response bias    It is important to note that increasing the sample size doe NOT remove or reduce a bias. The only  way to do this is to fix the sampling process used.            Additional Terms  ● An ​experimental unit​ is the person who is studied by the survey.  ● A t​ reatment ​ is a contiditon applied to the subject  ● The ​explanatory variable​ explains or influences the changes in a response variable  ● Response variable ​ is what is being measured by the study  ○ Basically, the explanatory variable is used to explain the response variable

×

×

### BOOM! Enjoy Your Free Notes!

×

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

Steve Martinelli UC Los Angeles

#### "There's no way I would have passed my Organic Chemistry class this semester without the notes and study guides I got from StudySoup."

Anthony Lee UC Santa Barbara

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

Steve Martinelli UC Los Angeles

Forbes

#### "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

#### STUDYSOUP CANCELLATION 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 support@studysoup.com

#### STUDYSOUP REFUND POLICY

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: support@studysoup.com

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 support@studysoup.com