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26134  Business Statistics 26134  Business Statistics

26134 Business Statistics - PowerPoint Presentation

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26134 Business Statistics - PPT Presentation

MahritaHarahaputseduau Week 1 Tutorial Foundation Mathematics for Business Statistics The objective of this tutorial is for students to identify gaps in their maths knowledge early so they dont make errors and little mistakes that will cost them marks in other assessments ID: 779436

week marks question threshold marks week threshold question note concept data population multiply 00cb02 statistics exponents numerator inference sign

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Slide1

26134 Business Statistics

Mahrita.Harahap@uts.edu.auWeek 1 Tutorial: Foundation Mathematics for Business Statistics The objective of this tutorial is for students to identify gaps in their maths knowledge early so they don’t make errors and little mistakes that will cost them marks in other assessments. Please go through the PowerPoint file “Calculator”.

1

WHAT IS STATISTICS?

Slide2

BSTATS-KEY ASSESSMENT ITEMS

2

“THRESHOLD CONCEPTS”

THRESHOLD

WEEK

THRESHOLD CONCEPT 1 (TH1): Identifying relevant data, understanding measurement properties of data

WEEK 1

THRESHOLD CONCEPT 2 (TH2): Understanding Data and summarizing data

WEEK

2

THRESHOLD CONCEPT 3 (TH3): Relating variables and analyzing relationships between variables

WEEKS 3-5

THRESHOLD CONCEPT 4 (TH4): Theoretical foundation of statistical inference-Understanding events and using data to calculate the probability of occurrence of an event.

WEEK 7

THRESHOLD CONCEPT 5 (TH5): Theoretical foundation of statistical inference: Collecting samples and drawing inference

WEEK 10

THRESHOLD CONCEPT 6 (TH6): Theoretical foundation of statistical inference: Building interval estimates and constructing hypothesis for statistical inference

WEEKS 11-12

Slide3

THRESHOLD ASSESSMENT

3

TH 1

TH 5

TH 3

TH 4

TH 2

TH 6

WEEK 5

WEEK 9

WEEK

11

QUIZ 1

QUIZ 2

FINAL EXAM

“MAKE-UP QUIZ

MARKS

10 marks

10 marks

20 marks

10 marks

10 marks

20 marks

Assignment

20 marks

100 marks

= alternate opportunity to achieve marks for TH1 and TH2

= alternate opportunity to achieve marks for TH3 and TH4

Slide4

4

Slide5

Student Resources

UPASS - is a voluntary “study session” where you will be studying the subject with other students in a group. It is led by a student who has previously achieved a distinction or high distinction in that subject, and who has a good WAM. You can sign up for U:PASS sessions in My Student Admin https://onestopadmin.uts.edu.au/. Note that sign up is not open until week 1, as it’s voluntary and only students who want to go should sign upTo Sign Up to these groups go to this website: helps-booking.uts.edu.auMaths Study Center @ CB04.03.331Free drop-in one on one consultation tutoring

on math/stats related questions 11am to 5pm on weekdaysOnline resources such as youtube or www.khanacademy.org Discussion Board on UTS Online

5

Mon

09:00-10:00

CB02.06.37

Mon

10:00-11:00

CB02.06.37

Mon

11:00-12:00CB02.06.37

Mon14:00-15:00CB02.06.37Mon16:00-17:00CB02.06.37Mon17:00-18:00CB02.06.37Tue18:00-19:00

CB02.06.37Wed09:00-10:00CB02.06.37Wed11:00-12:00CB05C.01.015Wed12:00-13:00CB05C.01.015Wed

15:00-16:00CB05C.02.054

Slide6

Question 1: Order of mathematical operation

6

BIDMAS: Brackets, Indices, Division and Multiplication, Addition and Subtraction

NOTE: in b), when there is a divisor line, it instructs you to treat the quantity above the numerator as if it were enclosed in a parenthesis, and to treat the quantity below the numerator as if it were enclosed in yet another parenthesis.

Slide7

Question 2: Converting Units of Measure

a) 12.5 hours + 43.2 minutes = b) 26km/h + 4 m/s =

7

NOTE: To turn hours into minutes, there are 60 minutes in an hour, so multiply 12.5 by 60 and you will get 12.5 hours in terms of minutes.

NOTE: There are 1000 meters in a kilometer. So multiply 26 by 1000 to give you 26km in terms of meters. There are 3600 seconds in an hour, so to turn m/h into m/s, divide 26000 by 3600 to give you 26000m/h in terms of m/s.

Slide8

Question 3: Square Root

8

REMEMBER: (from q1) when there is a divisor line, it instructs you to treat the quantity above the numerator as if it were enclosed in a parenthesis, and to treat the quantity below the numerator as if it were enclosed in yet another parenthesis.

Slide9

Question 4: Indices Rules

9

NOTE: in d), mathematicians define y

^0 = 1 in order to make the laws of exponents work even when the exponents can no longer be thought of as repeated multiplication. For example, (y^3)(y^5) = y^8 because you can add exponents. In the same way (y^0)(y^2)=y^2 by adding exponents. But that means that y^0 must be 1 because when you multiply y^2 by it, the result is y^2. Only y^0 = 1 makes sense here.

Slide10

Question 5: Converting Decimals to Percentage to Fractions

10

NOTE: this is a very fundamental concept and often very handy to simplify and solve problems. From decimals to percentage, multiply by 100. From decimals to fractions, divide the decimal form by 1 then

multiply top and bottom of this fraction by the value that will give us an integer in the

numerator

.

(For example, if there are two numbers after the decimal point, then use 100, if there are three then use 1000, etc

.). Then simplify the fraction.

Slide11

Question 6: Mathematical Notation

11

Because superscripted exponents

like 10

7

 cannot always be conveniently displayed, the letter 

E

 

is

often used to represent "times ten raised to the power of" (which would be written as "× 10

n

") and is followed by the value of the exponent; in other words, for any two real numbers m and n, the usage of "mEn" would indicate a value of m × 10n.

Slide12

Question 7: Factorial !

If n=10, p=5 , y=0, Find n!, p! and y! For the same values calculate p!/[(n-p)!]=

12

NOTE: To find out why 0!=1 go to http://mathforum.org/library/drmath/view/57128.html

Slide13

Question 8: Exponential functions

13

On the calculator:

Slide14

In statistics we usually want to statistically analyse a population but collecting data for the whole population is usually impractical, expensive and unavailable. That is why we collect samples from the population (

sampling

) and make inferences about the population parameters using the statistics of the sample (inferencing) with some level of accuracy (confidence level).

A

population

is a collection of all

possible individuals, objects, or measurements of interest. A

sample

is a

subset

of the population of interest.