# Preface  (Page 2/2)

 Page 2 / 2

## Pedagogical foundation and features

• Examples are placed strategically throughout the text to show students the step-by-step process of interpreting and solving statistical problems. To keep the text relevant for students, the examples are drawn from a broad spectrum of practical topics; these include examples about college life and learning, health and medicine, retail and business, and sports and entertainment.
• Try It practice problems immediately follow many examples and give students the opportunity to practice as they read the text. They are usually based on practical and familiar topics, like the Examples themselves .
• Collaborative Exercises provide an in-class scenario for students to work together to explore presented concepts.
• Using the TI-83, 83+, 84, 84+ Calculator shows students step-by-step instructions to input problems into their calculator.
• The Technology Icon indicates where the use of a TI calculator or computer software is recommended.
• Practice, Homework, and Bringing It Together problems give the students problems at various degrees of difficulty while also including real-world scenarios to engage students.

## Statistics labs

These innovative activities were developed by Barbara Illowsky and Susan Dean in order to offer students the experience of designing, implementing, and interpreting statistical analyses. They are drawn from actual experiments and data-gathering processes, and offer a unique hands-on and collaborative experience. The labs provide a foundation for further learning and classroom interaction that will produce a meaningful application of statistics.

Statistics Labs appear at the end of each chapter, and begin with student learning outcomes, general estimates for time on task, and any global implementation notes. Students are then provided step-by-step guidance, including sample data tables and calculation prompts. The detailed assistance will help the students successfully apply the concepts in the text and lay the groundwork for future collaborative or individual work.

## Ancillaries

• Instructor’s Solutions Manual
• Webassign Online Homework System
• Video Lectures delivered by Barbara Illowsky are provided for each chapter.

## Senior contributing authors

 Barbara Illowsky De Anza College Susan Dean De Anza College

## Contributing authors

 Abdulhamid Sukar Cameron University Abraham Biggs Broward Community College Adam Pennell Greensboro College Alexander Kolovos Andrew Wiesner Pennsylvania State University Ann Flanigan Kapiolani Community College Benjamin Ngwudike Jackson State University Birgit Aquilonius West Valley College Bryan Blount Kentucky Wesleyan College Carol Olmstead De Anza College Carol Weideman St. Petersburg College Charles Ashbacher Upper Iowa University, Cedar Rapids Charles Klein De Anza College Cheryl Wartman University of Prince Edward Island Cindy Moss Skyline College Daniel Birmajer Nazareth College David Bosworth Hutchinson Community College David French Tidewater Community College Dennis Walsh Middle Tennessee State University Diane Mathios De Anza College Ernest Bonat Portland Community College Frank Snow De Anza College George Bratton University of Central Arkansas Inna Grushko De Anza College Janice Hector De Anza College Javier Rueda De Anza College Jeffery Taub Maine Maritime Academy Jim Helmreich Marist College Jim Lucas De Anza College Jing Chang College of Saint Mary John Thomas College of Lake County Jonathan Oaks Macomb Community College Kathy Plum De Anza College Larry Green Lake Tahoe Community College Laurel Chiappetta University of Pittsburgh Lenore Desilets De Anza College Lisa Markus De Anza College Lisa Rosenberg Elon University Lynette Kenyon Collin County Community College Mark Mills Central College Mary Jo Kane De Anza College Mary Teegarden San Diego Mesa College Matthew Einsohn Prescott College Mel Jacobsen Snow College Michael Greenwich College of Southern Nevada Miriam Masullo SUNY Purchase Mo Geraghty De Anza College Nydia Nelson St. Petersburg College Philip J. Verrecchia York College of Pennsylvania Robert Henderson Stephen F. Austin State University Robert McDevitt Germanna Community College Roberta Bloom De Anza College Rupinder Sekhon De Anza College Sara Lenhart Christopher Newport University Sarah Boslaugh Kennesaw State University Sheldon Lee Viterbo University Sheri Boyd Rollins College Sudipta Roy Kankakee Community College Travis Short St. Petersburg College Valier Hauber De Anza College Vladimir Logvenenko De Anza College Wendy Lightheart Lane Community College Yvonne Sandoval Pima Community College

## Sample ti technology

Uttam
How can I calculate the Class Mark, Relative frequency and the cumulative frequency on a frequency table?
what is the important in business planning and economics
explain the limitation and scope of statistics
mahelt
statistics is limited to use where data can be measured quantitatively. statistics scope is wider such as in economic planning, medical science etc.
Gurpreet
can you send me mcq type questions
Yas
Umar
which books are best to learn applied statistics for data science/ML
Gurpreet
A population consists of five numbers 2,3,6,8,11.consists all possible samples of size two which can be drawn with replacement from this population. calculate the S.E of sample means
A particular train reaches the destination in time in 75 per cent of the times.A person travels 5 times in that train.Find probability that he will reach the destination in time, for all the 5 times.
0.237
Amresh
umesh
p(x=5)= 5C0 p^5 q^0 solve this
Amresh
umesh
ok
umesh
5C0=1 p^5= (3/4)^5 q^0=(1/4)^0
Amresh
Hint(0.75 in time and 0.25 not in time)
kamugi
what is standard deviation?
It is the measure of the variation of certain values from the Mean (Center) of a frequency distribution of sample values for a particular Variable.
Dominic
what is the number of x
10
Elicia
Javed Arif
Jawed
how will you know if a group of data set is a sample or population
population is the whole set and the sample is the subset of population.
umair
if the data set is drawn out of a larger set it is a sample and if it is itself the whole complete set it can be treated as population.
Bhavika
hello everyone if I have the data set which contains measurements of each part during 10 years, may I say that it's the population or it's still a sample because it doesn't contain my measurements in the future? thanks
Alexander
Pls I hv a problem on t test is there anyone who can help?
Peggy
Dominic
Bhavika is right
Dominic
what is the problem peggy?
Bhavika
hi
Sandeep
Hello
hi
Bhavika
hii Bhavika
Dar
Hi eny population has a special definition. if that data set had all of characteristics of definition, that is population. otherwise that is a sample
Hoshyar
three coins are tossed. find the probability of no head
three coins are tossed consecutively or what ?
umair
umair
or .125 is the probability of getting no head when 3 coins are tossed
umair
🤣🤣🤣
Simone
what is two tailed test
if the diameter will be greater than 3 cm then the bullet will not fit in the barrel of the gun so you are bothered for both the sides.
umair
in this test you are worried on both the ends
umair
lets say you are designing a bullet for thw gun od diameter equals 3cm.if the diameter of the bullet is less than 3 cm then you wont be able to shoot it
umair
In order to apply weddles rule for numerical integration what is minimum number of ordinates
excuse me?
Gabriel
why?
didn't understand the question though.
Gabriel
which question? ?
We have rules of numerical integration like Trapezoidal rule, Simpson's 1/3 and 3/8 rules, Boole's rule and Weddle rule for n =1,2,3,4 and 6 but for n=5?
John
Someone should help me please, how can I calculate the Class Mark, Relative frequency and the cumulative frequency on a frequency table?
IJOGI
geometric mean of two numbers 4 and 16 is:
10
umair
really
iphone
quartile deviation of 8 8 8 is:
iphone
sorry 8 is the geometric mean of 4,16
umair
quartile deviation of 8 8 8 is
iphone
can you please expalin the whole question ?
umair
mcq
iphone
h
iphone
can you please post the picture of that ?
umair
how
iphone
hello
John
10 now
John
how to find out the value
can you be more specific ?
umair
yes
KrishnaReddy
what is the difference between inferential and descriptive statistics
descriptive statistics gives you the result on the the data like you can calculate various things like variance,mean,median etc. however, inferential stats is involved in prediction of future trends using the previous stored data.
umair
if you need more help i am up for the help.
umair
Thanks a lot
Anjali
Inferential Statistics involves drawing conclusions on a population based on analysis of a sample. Descriptive statistics summarises or describes your current data as numerical calculations or graphs.
fred
my pleasure😊. Helping others offers me satisfaction 😊
umair
inferential statistics the results of the statistical analysis of the sample data of the population are used for generalization or decision making about the population why descriptive statistics, the analyzed data are presented without generalization or decision making about the population.
IJOGI