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by: WB

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# week 1 : elementary statistics course overview MAT117

Marketplace > Pace University > Mathematics (M) > MAT117 > week 1 elementary statistics course overview
WB
Pace
GPA 3.83
Elementary statistics
Dr. Glenn Miller

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These are updating notes from Dr. Miller's lectures and the textbook. Enjoy and feel free to reach out with any questions or if you need a study buddy!
COURSE
Elementary statistics
PROF.
Dr. Glenn Miller
TYPE
Class Notes
PAGES
6
WORDS
CONCEPTS
elementary statistics, Mathematics
KARMA
25 ?

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## Popular in Mathematics (M)

This 6 page Class Notes was uploaded by WB on Saturday September 12, 2015. The Class Notes belongs to MAT117 at Pace University taught by Dr. Glenn Miller in Fall 2015. Since its upload, it has received 63 views. For similar materials see Elementary statistics in Mathematics (M) at Pace University.

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## Reviews for week 1 : elementary statistics course overview

Why didn't I know about this earlier? This notetaker is awesome, notes were really good and really detailed. Next time I really need help, I know where to turn!

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Date Created: 09/12/15
DATE 922015 Wednesday Course Overview Statistics Descriptive statistics Inferential statistics Three characteristics of data sets Measure of central tendencv Confidence intervals Hypothesis tests Measure of disoersion Shape of the distribution Correlation and regression statistical techniques for analyzing data for two or more variables a Descriptive statistics gathering presenting summarizing Three characteristics of data sets 1 Measure of central tendency mean the average as the expected value median consistent more predictable larger range more variation Ex Student A scores 78 80 82 81 79 Student B scores 100 70 80 60 90 Conclusions Student A scores more consistent student B s scores have larger range Measure of dispersion spread rangehighest lowest standard deviation SD on average how far away from the mean are the observation the average distance from the middle for the values in the data set s XXX XV N 1 SSD 2sum of fsample mean Nnumber of scores in sample student A SD516 student B SD516 Shape of the distribution the shape of the graph of the relative frequency distribution Ex Student Age Frequency Relative frequency 18 5 52025 19 9 45 20 3 15 4 21 2 10 22 1 5 Total 20 100 Age of students 50 40 30 20 10 0 l Age of students Measure of position a characteristic of an observation in the data set percentile zSCOrestandard score How many standard deviations away from the mean an observation is and in which direction Notice any zscore over two is considered to be quotan outlier or a weirdo z x X Zzscore Xthe observation fsample mean 5 2 SD Ex Mean80 SD16 what is zscore for score of 90 lgtz9 80 625 16 Ex 10 of Americans are left handed 11 out of 20 mathematicians are lefties Conclusions Mean 20 o 102 so m z 13 kg 671 13 Probability amp Probability Distributions use statistic from a sample to estimate a bigger set Ex consider the sum of two dice Sum of dice Probability relative frequency 136 236 336 436 536 636 536 LDOONOWU lbUUN 436 0 336 236 12 136 Total 100 Normal distribution heights weights IQ scores Binomial distribution Central limit theorem linking results with a sample and the characteristics of the underlying population DATE 922015 Wednesday Course Overview Statistics Descriptive statistics Inferential statistics Three characteristics of data sets Measure of central tendencv Confidence intervals Hypothesis tests Measure of disoersion Shape of the distribution Correlation and regression statistical techniques for analyzing data for two or more variables a Descriptive statistics gathering presenting summarizing Three characteristics of data sets 1 Measure of central tendency mean the average as the expected value median consistent more predictable larger range more variation Ex Student A scores 78 80 82 81 79 Student B scores 100 70 80 60 90 Conclusions Student A scores more consistent student B s scores have larger range Measure of dispersion spread rangehighest lowest standard deviation SD on average how far away from the mean are the observation the average distance from the middle for the values in the data set s XXX XV N 1 SSD 2sum of fsample mean Nnumber of scores in sample student A SD516 student B SD516 Shape of the distribution the shape of the graph of the relative frequency distribution Ex Student Age Frequency Relative frequency 18 5 52025 19 9 45 20 3 15 4 21 2 10 22 1 5 Total 20 100 Age of students 50 40 30 20 10 0 l Age of students Measure of position a characteristic of an observation in the data set percentile zSCOrestandard score How many standard deviations away from the mean an observation is and in which direction Notice any zscore over two is considered to be quotan outlier or a weirdo z x X Zzscore Xthe observation fsample mean 5 2 SD Ex Mean80 SD16 what is zscore for score of 90 lgtz9 80 625 16 Ex 10 of Americans are left handed 11 out of 20 mathematicians are lefties Conclusions Mean 20 o 102 so m z 13 kg 671 13 Probability amp Probability Distributions use statistic from a sample to estimate a bigger set Ex consider the sum of two dice Sum of dice Probability relative frequency 136 236 336 436 536 636 536 LDOONOWU lbUUN 436 0 336 236 12 136 Total 100 Normal distribution heights weights IQ scores Binomial distribution Central limit theorem linking results with a sample and the characteristics of the underlying population

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