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1 review
by: Ang Judd

21

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9

# Math 2040 Math 2040

Ang Judd
SUU

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Chapters 1-3
COURSE
PROF.
Said Bahi
TYPE
Class Notes
PAGES
9
WORDS
CONCEPTS
KARMA
Free

## 1

1 review
"I was sick all last week and these notes were exactly what I needed to get caught up. Cheers!"
Anais Zemlak

## Popular in Math

This 9 page Class Notes was uploaded by Ang Judd on Saturday January 23, 2016. The Class Notes belongs to Math 2040 at Southern Utah University taught by Said Bahi in Winter 2016. Since its upload, it has received 21 views. For similar materials see Business Statistics in Math at Southern Utah University.

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## Reviews for Math 2040

I was sick all last week and these notes were exactly what I needed to get caught up. Cheers!

-Anais Zemlak

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Date Created: 01/23/16
Chapter 1 Objective of Statistics: Study of populations EX) Population: Set of all patients in a hospital List of all members of a population of interest Frame Census: A survey that includes all the elements or units in the frame. Sample: A subset of the population which is used to gain insight about the population. A sample represents the entire population. EX) Study of the age of the population Sample  Average age  Statistic (KNOWN, CHANGES WITH SAMPLE) Population Parameters: A numerical description of a population’s characteristic Population Average age  Parameter (UNKNOWN, FIXED) Statistic: A factor characteristic of a sample. Branches of Statistics Examples of Descriptive Statistics -Frequency Distribution -Central Tendency Descriptive Statistics Inferential -Mean Statistics -Median -Collect Data -Mode -Organize Data -Measures of Dispersion -Graph Data -Range -Variance -Standard Deviation Inferential Statistics: To make reasonable estimates about population characteristics. X of the surveyed  Statistic Chapter 2 Data are either qualitative or quantitative. Qualitative: Categorical Data; Consists of labels or descriptions of traits (T- number, Fav. Pizza) Quantitative: Consists of counts or measurements (Height, Weight) Quantitative Data has two sub-types: Continuous data: are the quantitative data that can take on any value in a given interval and are usually measurements. Discrete Data: are quantitative data in which the observations are restricted of a set of values; no decimals (1,2,3,4) Levels of Measurement: Nominal. Ordinal, Interval, Ratio Nominal: Qualitative; no mathematical operation possible (fav. Food) Ordinal: Qualitative; can be ordered (concert seats) Interval: Quantitative; order+differences are possible (birth years in a family) Ratio: Quantitative; order+differences+ratios are possible; Zero point = an absence (ages) EX) Time duration of commuting X1= 5 min X2-X1= 15 min X2= 20 min X2/X1= 20/5= 4 X3= 0 min (X2took 4 times longer than X ) 1 Time Series: Observe a variable (X) in time; used to follow trends T X X 1 T1 X2 T2 X3 T3 Xn Tn *ex: Graph (excel) time series table 2.4 pg 51* Stationary Process: the time series varies around some central value and has approximately the same variation over the series. Nonstationary Process: the time series possess a trend- the tendency for the series to either or increase over time. Chapter 3 Frequency Distribution for Qualitative Variables EX) a,a,a,b,c,b,a,c,d Frequency Table X F A 4 B 2 C 2 D 1 *ex: pg 75 table 3.3* Graphing Qualitative Data: Bar & Pie Chart 10 n=total of sample 8 6 *Businesses don’t care about how Frequency many people don’t like the price, 4 instead they care about the 2 percentage of customers that don’t 0 like the price* *ex: 2.7* CD BL Cplan S Heat Relative Frequency Rf=f/n Student's Housing Types 50% 40% 30% 41% 31% 20% Frequency 10% 18% 10% 0% Housing Type Housing Frequen Relative Type cy Frequen cy Apartme 20 20/49 nt 41% Dorm 15 15/49 31% House 9 9/49 18% Other 5 5/49 5% EX) 2.10 30 25 Housing Sample A Sample B 20 15 Type 10 Sample A Apartment 20 13 5 Dorm 15 24 0 Sample B House 9 6 Other 5 7 *You can also stack the two samples when graphing* 50 40 30 20 10 Sample B 0 Sample A X F RF Angle Apt 20 20/49 or 41% 360 x 0.41 Dorm 15 15/49 or 31% 360 x 0.31 Hous 9 9/49 or 18% 360 x 0.18 e Other 5 5/49 or 10% 360 x 0.10 *You need the table on your homework, even if you use excel. You need to show your work!* Sample A Apartment Dorm 10% House 18% 41% Other 31% Frequency Distribution for Quantitative Data EX) 25,31,29,31,43,17,31,25,45,25,16,25,25 -Create classes, then find the frequency of each class (0-10,10-20, etc.) You don’t want too few!!! (4 classes) Rules for number of classes: √ n(observations) n= 13 √13 = 3.3 = 4 √n(observations) 2 (2 =1, 2 =2, 2 =4, 2 =8, 2 =16) -Determine the class width (range/# of classes) W= highest value-lowest value/ number of classes *Round up to the nearest whole number!!* EX) 45-16/4=7.258 W=8 Classe Class f s Boundry 16-23 15.5-23.5 2 24-31 23.5-31.5 9 32-39 31.5-39.5 0 40-47 39.5-47.5 2 Stem and Leaf Graph (Quantitative Data) *Not all that great for large data sets* EX) 77, 92, 91, 105, 115, 110 Key Stem Leaf Stem Leaf 7 7 7 7 7 7 9 2 9 1, 2 9 1 10 5 10 5 11 0, 5 11 5 11 0 Ordered Array Objective: ordering a set of observations in either ascending (rank) or descending (reverse rank) order. Dot Plot (Quantitative Data) *Useful for when you’re interested in where the data are clustered and which values occur more often.* *Good if you have a lot of data that repeats* EX) Plot 25, 31, 29, 31, 25, 31, 45, 17, 21 __l_____l_____l_____l__ Uploading FileOptionsAdd-ins Manage excel add-ins”Go”HomeDataData AnalysisHistogramFigure it out from there (easy)

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