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Intro to Statistics Chapter 1 Notes

by: Michaela Zerbo

Intro to Statistics Chapter 1 Notes STAT 145

Marketplace > Rochester Institute of Technology > Statistics > STAT 145 > Intro to Statistics Chapter 1 Notes
Michaela Zerbo
GPA 3.1

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Will be on Exam #1 and display basic statistics and terms
Intro to Stats
Professor Nilay Sapio
Class Notes
intro to statistics
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This 7 page Class Notes was uploaded by Michaela Zerbo on Tuesday September 6, 2016. The Class Notes belongs to STAT 145 at Rochester Institute of Technology taught by Professor Nilay Sapio in Fall 2016. Since its upload, it has received 178 views. For similar materials see Intro to Stats in Statistics at Rochester Institute of Technology.


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Date Created: 09/06/16
 1  STAT 145  Introduction to Statistics 1  Chapter 1 ­ Data Collection  Terms     ​ ormulas          1.1 Introduction to the Practice to Statistics    Objectives: ​Definitions and process of statistics / Qualitative vs. Quantitative    Statistical Process:    Population:​ An entire group of people, things, or  events that has at least one common trait.      Sample:​ A smaller number of observations taken  from a population          P​arameter: A ​  measure obtained from the ​entire  population. This is not practical.     P​arameters, the value related to  P ​pulations  What we want      S​tatistics: ​A measure obtained from the sample.     S​tatistics, the values pertaining to ​ S​amples  What we get             2        Variables:    Quantitative (Numeric): ​Provides  numerical measures of individuals        Discrete vs. Continuous                     Interval: ​Ordered categories with meaningful difference in values (no true 0)  Ratio: ​Interval measurement with meaningful ratio of values (0 means lack of quantity)  Nominal: C ​ ategories ­ Names ­ Titles  Ordinal: ​Ordered categories    Examples:  Hair Color ­ ​N​ominal  Country ­ N ​ ​ominal  Value of a Liquid ­ ​R​atio  Men’s Clothing Size ­ ​R​atio/​I​nterval/​O​rdinal ­ depends how view  Degree ­ O ​ ​rdinal                           3                      Which is better?  It depends.  Observation is more cost and time effective  Experimental can identify causal relationships              1.2 Observational Studies vs. Designed Experiments  Objectives: R ​ ecognize different types of studies             4      1.3 Introduction to the Practice to Statistics  Objectives: U ​ nderstand a simple, random sample      1.  ​S​ample: Students sitting in the last row / ​P​opulation: All STAT 145 students  2.  ​S​ample: First 200 customers arrived in a stadium / ​P​opulation: Stadium customers  3.  ​S​ample: Students taught in room 145 / ​P​opulation: All RIT students  4.  ​S​ample: People in Costco / ​P​opulation: New York Public      Random Sampling:      Random Sampling: ​Selecting individuals  from a population through chance          Simple Random Sampling: ​As if every  member of the sample has an equal chance  of being picked              How do I obtain a Simple Random Sample?                         5  1.4 Other Sampling Methods  Objectives: ​Understand a stratified, systematic, and a cluster sample          Stratified Sample:   ● Separate population into a non­overlapping group called ​Strata  ● Obtain simple random sample from each stratum  ● Individuals in each stratum should share similar attributes        Systematic Random Sample:   ● Select a number (x)  ● Randomly select a number  between 1 and x  ● Survey every x​ th​individual until  desired sample size      Cluster Sample:   ● Randomly select a  collection/group  ● Include all individuals in the  selected group for the sample      Convenience  Sample:   ● Individuals are easily obtained  ● Not random ­ Unreliable results  ● Sample is not representative       Multistage Sample:   ● Use a combo of sampling methods               6    Examples:  1. To determine the customer opinion of its customer service response, Cosco randomly  selects 3 days during a certain week and surveys all customers in register 5. (​Cluster​)    2. To understand the utilization of the No Voice Zone, RIT randomly selects 150  students using its roster. (S ​ imple Random​)    3. Starbucks selects every 6th customer that walks through until they obtain the views  about their new coffee display. (​Systematic Random) ​     1.5 Other Bias in Sampling  Objectives: ​Understand the source of bias    The Three Sources of Bias:    1.  Sampling Bias:  Sampling techniques used tends to favor one part of the population over another    Ex. ​Public opinions polls done through phone calls may excluded those without a home  phone or those who are homeless.       2. Nonresponse Bias:  What happens when individuals selected in the sample who do not respond have  different opinion than those who respond?              Follow­Ups                                7  3. Response Bias:  When the answers do not reflect the true feelings of the respondent  HOW?  1. Interview error  2. Data entry error  3. Wrong wording        1.6 Design of Experiments  Objectives: ​Characteristics of Experiments     Experiments are a controlled study that determines the effects of factors on a response  variable.             


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