Statistics - Lecture notes chapter 1 to 8 PDF

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lectures notes and practice problems with professor Stephenson...

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Course: Semester Ticket Class time Online access for MyStatLab Online access CANVAS Instructor Faculty e-mail Office hours Math Center Number of units

COURSE SYLLABUS Math 10 Main (Pink) Math 10 Fall 2019 62400 4:30 pm to 5:45 pm BSTIC 112 https://ivc.instructure.com/login/ldap https://canvas.ivc.edu/login/ldap Prof. Gabrielle Stephenson [email protected] Online: TTH 3pm to 5:30 pm http://academics.ivc.edu/mathcenter/Pages/default.aspx 3 (letter grade)

Course description: This course is designed to provide information about statistical methods as applied to descriptive statistics and inferential statistics. It is a course with co-requisite support. Required text: Mario F. Triola, Elementary Statistics 13th Edition. MyStatLab access needs to be done with Elementary Statistics with Integrated Review 13th Edition Triola, Mario Textbook ISBN-13: 9780134462455 Sub-series: Integrated Review Grading procedures: THIS CLASS IS NOT GOING TO BE CURVED ¾ Homework (10 sets, 10 points each) 100 points and 15% of overall grade (Inside Pearson) ¾ 10 online quizzes (10 points each) 100 points and 15% of overall grade (Inside Pearson) ¾ Three in-class exams worth 15% of the overall grade each: x Test 1 in-person Chapters 1 and 2 x Test 2 in-person Chapters 3, 4, and 5 x Test 3 in ʹperson Chapters 6, 7, and 8 ¾ Cumulative (chapters 1-12) in-class final 100 points and 25% of overall grade ¾ Discussion Board Postings 0 points (Inside IVC CANVAS) ¾ Entry/Exit Surveys zero points (Inside IVC CANVAS) ¾ Contract (Inside IVC CANVAS) zero points) ¾ Final drill zero points (Inside Pearson) ¾ Grades: 90-100% A 80-89.99% B 70-79.99 % C 60-69.99% D 59.99% and less is F Homework (MyStatLab): No late homework will be accepted for any reason. You need to do the computer problems under each chapter in the Pearson system MyStatLab. To do these problems, go to homework, click on the problems, and do them. You do not need to submit anything in paper but you have deadlines to finish homework. Quizzes (MyStatLab): A quiz will be given after the completion of every chapter online. These quizzes are taken online under Assignments in Pearson within a deadline (5 minutes to midnight on the due date). You can submit these quizzes only once in one sitting. A missed quiz will earn a score of 0 points (no exceptions). There will be no make-ups for missed quizzes. Final: A cumulative final exam must be taken in-class during the last week of classes. Calculators: A graphing calculator is required for this class (TI-83, TI-83+ or TI 84). You may use your calculator during the tests and quizzes. I have VERY detailed instructions per chapter under CANVAS about how to use your calculator. Please watch them to be successful in this class. There will be graphing calculators for use during class time in class.

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Introduction to Statistics

Lesson 1.1: Statistical In general, we want to be able to think critically about statistics and not focus on calculations in statistics, though that will be necessary as we progress. The following items help us to understand the thought process we need to harness statistics: x

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Some common concepts that we will run into can be found here: x

Data: _________________________________________________________________

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Statistics: ______________________________________________________________ ______________________________________________________________________ ______________________________________________________________________

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Population: ____________________________________________________________

x

Census: _______________________________________________________________

x

Sample: _______________________________________________________________

Le look an eample

Population: _________________________________________________________________ Sample: ____________________________________________________________________

________________________, and __________________________.

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The process involved in conducting a statistical study consists of ______________________, Page

and Critical Thinking

It is important to know that the sampling methods and use of randomization will be discussed in section 1.3 but sound sampling is essential for good results in a statistical study. In general, it is bad practice to use voluntary response samples although their use is common.

Voluntary response sample: _____________________________________________________ Some examples of voluntary response samples: ________________________, ___________________________________ and _____________________________________.

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Le look a an eample of olnar repone ample

Example: USA Toda poed hi qeion on i ebie Ho ofen do o eek medical informaion online Of  Inerne er ho choe o repond  of hem reponded ih freqenl x

What term is used to describe this type of survey in which the people surveyed consist of those who decided to respond? __________________________________________

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What is wrong with this type of sampling method? _____________________________________________________________________ _____________________________________________________________________

When analyzing data, we must be careful of the potentia _____________________________________________________________________

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Lesson 1.2: Types of A major use of statistics is to collect and use sample data to make conclusions about populations. We should know and understand the meanings of the terms statistics and parameter as defined below. We will describe a few different types of data, which will determine the statistical methods we use in our analysis. Parameter/Statistic:  A parameter is________________________________________________ _____________________________________________________________  A statistic is __________________________________________________ _____________________________________________________________

Identify the population and sample. Is 44.5% a statistic or parameter? Parameter:__________________________________________________________________ Statistic: ____________________________________________________________________ ____________________________________________________________________________

We also need to know the difference between quantitative data and categorical data, which distinguish between different types of numbers.

Quantitative/Categorical Some data are numbers representing counts or measurements (such as IQ score of 135), whereas others are attributes (such as eye color of green or brown) that are not counts or measurements. The terms quantitative data and categorical data distinguish between these types. Quantitative (or numerical) data________________________________________.

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Categorical (or qualitative or attribute) data _______________________________.

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Data

Example 2: Identify each of the following as quantitative data or categorical data. _________________

a. The plaele con in Daa Se  Bod Daa in Appendi B

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b. The cigaree brand in Daa Se  Cigaree Conen in Appendi B

_________________

c. The color of he MM candie in Daa Se  MM Weigh in Appendi B

_________________

d. The eigh of he MM candie in Daa Se  MM Weigh in Appendi B

Discrete/Continuous Quantitative data can be further described by distinguishing between discrete and continuous types. Discrete data result when __________________________________________________ ____________________________________________________________________________ (If there are infinitely many values, the collection of values is countable if it is possible to count them individually, such as the number of tosses of a coin before getting tails.) Continuous (numerical) data result from _________________________________________ ____________________________________________________________________________. (That is, it is impossible to count the individual items because at least some of them are on a continuous scale, such as lengths of distances from 0 cm to 12 cm.)

Example 3: Which of the following describe discrete data or continuous data? a. The numbers of people surveyed in each of the next several years for the National Health and Nutrition Examination Surveys _______________________________ b. The exact foot lengths (measured in cm) of a random sample of statistics students ____________________________________ c. The exact times that randomly selected drivers spend texting while driving during the

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past 7 days ________________________________

Levels of Measurement: Another common way to classify data is to use four levels of measurement: Nominal, Ordinal, Interval and Ratio. These levels help us to figure out what procedure to use. Make sure that you do not use computations and statistical methods that are not appropriate for the data. Seems like common sense but look at it this way for example, it does not make sense to compute the average of Social Security numbers because those numbers are data used for identification and are NOT representative of measurements or counts of anything. 1.

level of measurement:__________________________________________ ____________________________________________________________________.

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Examples of Nominal measurement:_______________________________________ level of measurement: __________________________________________ ____________________________________________________________________.

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Examples of Ordinal measurement: ______________________________________ level of measurement:___________________________________________ ____________________________________________________________________.

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Examples of Interval measurement: _______________________________________

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level of measurement:_____________________________________________ ____________________________________________________________________.

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Example of Ratio measurement: __________________________________________

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Example 4: Determine which of the four levels of measurement is most appropriate. a. U.S. News & World Report periodically provides its ranking of national universities, and in a recent year the ranks of Princeton, Harvard, and Yale were 1, 2, and 3 respectively. __________________________________ b. For the presidential election of 2016, ABC News conducts an exit poll in which voters are asked to identify the political party (Democratic, Republican, and so on) that they registered with. _______________________________ c. Color of MM red orange ello bron ble green lied in Daa Se  MM Weigh in Appendi B ______________________________ d. In a study of fast food service times, a researcher records the time intervals of driveup customers

g when they place their order and ending when they receive

their order. _____________________________ e. The author rated the movie Star Wars: Force Awakens with 5 starts on a scale of 5 stars. ______________________________

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Read pags. 21 to 22 for information on Missing Data!

Lesson 1.3: Collecting Part 1: Basics of Design of Experiments and Collecting Sample Data Randomiaion ih placeboreamen grop i omeime called he gold andard because it is so effective.

This example describes an ___________________________ because subjects were given a treatment. Sometimes ethical, cost, time, and other considerations prohibit the use of an experiment. Sometimes it is better to observe past results to understand what we want to examine.

Statistical methods are driven by the data we collect. We typically obtain data from two distinct sources: observational studies and experiments. x

In an observational study, we _____________________ and ___________________ specific characteristics, but we do not attempt to __________________ the subjects being studied.

x

In an experiment, we apply some _____________________ and then proceed to observe its _____________________ on the subjects.

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Subjects in experiments are called _________________________.

Of the two, experiments are often better than observational studies because experiments typically reduce the chance of having the results affected by some variable that is not part of a study. We call that kind of variable a __________________________________. It is a

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variable that affects the other variables included in the study but is not included in the study.

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Sample Data

Le look a o inance

Design of Experiments should include: ________________________, ___________________, ___________________________. x

Replication: ___________________________________________________________

x

Blinding: ______________________________________________________________ ¾ Placebo effect: ___________________________________________________ ¾ Double-blind: ____________________________________________________

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Randomization: ________________________________________________________ _____________________________________________________________________

Ways to collect dataÆSampling Methods

Simple Random Sample (SRS): ___________________________________________

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____________________________________________________________________

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x

Systematic Sample: ____________________________________________________

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Convenience Sample: ___________________________________________________

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Stratified Sample: ______________________________________________________ _____________________________________________________________________

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Cluster Sample: ________________________________________________________ _____________________________________________________________________

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Multistage Sampling: ___________________________________________________

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Example 3: Identify which of these types of sampling is used: random, systematic, convenience, stratified or cluster.

Part 2: Beyond the basics Here we will discuss different types of observational studies and different ways of designing

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experiments.

Observational Studies: x

In a c

study, data are _____________________,

____________________, and ____________________ at one point in time, not over a period of time. x

In a retrospective (or case-control) study, data are collected from a ______________________ by going back in time (through examination of _________________, _____________________ and so on).

x

In a prospective (or longitudinal or cohort) study, data are collected in the ________________ from groups that share _________________________________ (such groups are called ________________________)

Experiments: Results of experiments can be ruined because of confounding which occurs in an experiment when the investigators are _____________________ to distinguish among the _____________ of different factors.

4 Types of Experimental Design: x

Completely Randomized Experimental Design: ____________________________________________________ ____________________________________________________ ____________________________________________________ Randomized Block Design: ¾ A block is _____________________________________________________ ¾ Form blocks or groups of subjects _________________________________

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¾ Randomly assign treatments to the subjects _________________________

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Matched Pairs Design: ___________________________________________________ Examples of matched pairs: ______________________ or ________________________

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Rigorously Controlled Design: ______________________________________________ _____________________________________________________________________

We cannot talk about sampling methods without mentioning sampling error. We can use good sampling methods and do everything correctly and still get wrong results. Here are the different types of sampling errors we could encounter: x

A sampling error (or random sampling error) occurs when the sample has been selected with a random method, but there is a ____________________________ between a sample result and the ______________ population result; such an error results from chance sample ______________________________.

x

Nonsampling error is the result of ______________________, including such factors as _________________________________________, ___________________________________, questions with _____________________ wording, false data provided by _________________, forming _______________________________, or applying statistical methods that are not ______________________________ for the circumstances. A nonrandom sampling error is the result of using a sampling method that is _________ random, such as using a ____________________________ or

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___________________________.

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Chapter 2: Summarizing and Graphing Data Section 2.1: Frequency Distributions for Organizing and Summarizing Data In chapter 1, we learned about context of data, source of data, sampling methods, conclusions and the implications of incorrect sampling. Now, we will encounter distributions of data and will be asked to organize and summarize large amounts of data into tables or graphs. We will also learn other methods of investigating the data we have but not until chapter 3. When we are working with large data sets, a frequency distribution is helpful in organizing and summarizing data. The purpose of a frequency distribution is to figure ot the natre of the data set. In order to better nderstand freqenc distribtions, lets look an example: Example 1: Identify the c s for the gien freqenc distribtion of McDonalds lunch drive-through service times (in seconds). The frequency distribution summarizes the drive-through times. For example, the first class in Table 2-2 has a frequency of 11, so 11 of the service times are between 75 seconds and 124 seconds, inclusive. Before we do too much, let us look at the vocabulary as we answer the question.