SlideShare a Scribd company logo
Lecture 13 - Revision for Test B
C2 Foundation Mathematics (Standard Track)
Dr Linda Stringer Dr Simon Craik
l.stringer@uea.ac.uk s.craik@uea.ac.uk
INTO City/UEA London
Outline
Lecture 8
Pythagoras’ Theorem and Trigonometry
Sine and Cosine rules, Areas
Lecture 9
Probability
Lecture 10
Mode, Median and Interquartile range
Mean, Absolute deviation, Standard deviation
Z-test
Lecture 11
T-test
Lecture 12
χ2 -test
Pythagoras’ Theorem
Only works in right-angled triangles.
a
b
c
a2
+ b2
= hyp2
sin, cos and tan ratios
Only works in right-angled triangles.
opp
adj
hyp A
tan(A) =
opp
adj
cos(A) =
adj
hyp
sin(A) =
opp
hyp
Angle rule
Works in any triangle.
a
bc
B C
A
A + B + C = 180
Sine rule
Works in any triangle.
a
bc
B C
A
a
sin A
=
b
sin B
=
c
sin C
Cosine rule
Works in any triangle.
a
bc
B C
A
a2
= b2
+ c2
− 2bc cos(A)
Area
Works in any triangle.
a
bc
B C
A
Area =
1
2
ab sin(C)
Probability
The sum of all probabilities is 1.
The probability an event A happens is denoted P(A) and is
a number between 0 and 1.
The probability A does not happen is 1 − P(A).
The probability A and B happens is P(A) × P(B).
The probability A or B happens is P(A) + P(B).
Probability trees
You can use a probability tree when there is more than one
event.
Draw different tiers of branches for different events, and
write the probability next to the branch.
Multiply probabilities along the branches (AND)
Add up the probabilities at the end of each branch (OR)
The total of all the probabilities at the end of the branches
should be 1
The probabilities for the second tier may be the same as
for the first tier, or they may be different
Probability tree - roll a fair die twice (or roll two fair
dice)
What is the probability that I roll two fours?
What is the probability that I roll no fours?
What is the probability that I roll exactly one four?
What is the probability that I roll at least one four?
First roll Second roll
P(4, 4) = 1
6 × 1
6 = 1
36
P(4, ¬4) = 1
6 × 5
6 = 5
36
P(¬4, 4) = 5
6 × 1
6 = 5
36
P(¬4, ¬4) = 5
6 × 5
6 = 25
36
¬4
¬4
5/6
41/6
5/6
4
¬4
5/6
41/6
1/6
Mode
The mode is the most frequent object in your data.
X = 5 8 -3 7 8 2 8
The mode of X is 8.
Y = 0 2 1 6 5 1 2 3
The modes of Y are 1 and 2.
Median
The median is the middle data.
X = 5 8 -3 7 8 2 8
Order the data
X = -3 2 5 7 8 8 8
7 × 1/2 = 3.5
Round up to 4.
The median of X is the fourth term 7.
Median
Y = 0 2 1 6 5 1 2 3
Order the data
Y = 0 1 1 2 2 3 5 6
8 × 1/2 = 4
Add the fourth term and the fifth term and divide by 2.
The median of Y is 2+2
2 = 2.
Interquartile range
First order the data, with values increasing from left to right.
We want to find two values: the first quartile Q1 and the
third quartile Q3.
Let n be the size of the data set (the number of values).
To find Q1 we multiply n by 1
4 . If n
4 is an integer (whole
number) then Q1 is the midpoint of the (n
4 )th value and the
(n
4 + 1)th value
If n
4 is not an integer then round it up to the nearest integer.
Q1 is the corresponding value.
To find Q3 we multiply n by 3
4 . If 3n
4 is an integer then Q3 is
the midpoint of the (3n
4 )th value and the (3n
4 + 1)th value
If 3n
4 is not an integer then round it up to the nearest
integer. Q3 is the corresponding value.
The interquartile range is Q3 − Q1.
Interquartile range
The interquartile range is the middle half of the data. Take the
ordered data
X = -3 2 5 7 8 8 8
Find Q1 :
7 × 1/4 = 1.75
Round up to 2.
The first quartile if X is the second term, Q1 = 2.
Find Q3 :
7 × 3/4 = 5.25
Round up to 6.
The third quartile if X is the sixth term, Q3 = 8.
The interquartile range is Q3 − Q1 = 8 − 2 = 6
Interquartile range
The interquartile range is the middle half of the data. Take the
ordered data
Y = 0 1 1 2 2 3 5 6
Find Q1 :
8 × 1/4 = 2
Add the second term and the third term and divide by 2.
The first quartile of X is Q1 = 1+1
2 = 1.
Find Q3 :
8 × 3/4 = 6
Add the sixth term and the seventh term and divide by 2.
The third quartile of X is Q3 = 3+5
2 = 4.
The interquartile range is Q3 − Q1 = 4 − 1 = 3
Mean
The mean is the average of the data.
¯x =
x
n
5 8 -3 7 8 2 8
¯x =
5 + 8 + (−3) + 7 + 8 + 2 + 8
7
=
35
7
= 5
Absolute deviation
The absolute deviation is the average distance of the data from
the mean.
AD =
|x − ¯x|
n
5 8 -3 7 8 2 8
Calculate |x − ¯x| (remember that we calculated ¯x = 5)
0 3 8 2 3 3 3
Add these values together and divide by the number of values
in the list
AD =
0 + 3 + 8 + 2 + 3 + 3 + 3
7
=
22
7
Standard deviation
5 8 -3 7 8 2 8
The standard deviation, σ, is a measure of spread.
First find the variance, σ2.
σ2
=
x2
n
− ¯x2
Calculate x2:
25 64 9 49 64 4 64
Add these values together, divide by the size of the data and
subtract the mean squared.
σ2
=
279
7
− 52
=
104
7
The standard deviation is the square root of the variance
σ = 3.85 to 2 d.p.
Structure of hypothesis tests
The Z-test, the T-test and the χ2-test all have the same
structure
Hypotheses (H0 and H1)
Critical value (look it up in a table, and for the Z-test and
T-test add a sketch showing rejection regions )
Test statistic (calculate)
Decision (accept/reject H0)
Conclusion (write a sentence)
The Z-test
The question will tell you the population mean µ and the
standard deviation of the population σ. It may also give you
information for your alternative hypothesis.
Write your null hypothesis H0 and your alternative
hypothesis H1.
Read your critical value off the table.This will depend on
your significance level and your alternative hypothesis.
You will be given a sample mean ¯x and the size of the
sample data n. Calculate your test statistic.
Z =
¯x − A
σ/
√
n
Compare the test statistic and the critical value. Decide to
accept or reject the null hypothesis. Write a concluding
sentence.
Example
The National Association of Florists say the perfect
sunflower should be 90cm tall with a standard deviation of
9.5cm. We grow 100 sunflowers with a mean height of 92
cm. We want to see whether or not our sunflowers are
perfect to a 5% level of significance.
H0 : µ = 90.
H1 : µ = 90.
We are doing a 2-tailed test. Reading off our table we get
critical values of −1.96 and 1.96.
The test statistic is 92−90
9.5/
√
100
= 2.11 to 2 d.p.
The test statistic 2.11 is bigger than the critical value 1.96
so we decide to reject the null hypothesis.
We conclude that our sunflowers are not perfect.
The T-test
The question will tell you the population mean µ. It will also
give you a small table of size n with some data. It may also
give you information for your alternative hypothesis.
Write your null hypothesis H0 and your alternative
hypothesis H1.
Read your critical value off the table.This will depend on
your significance level, your alternative hypothesis and the
degree of freedom of your data.
You will calculate the sample mean ¯x and the sample
standard deviation s. Calculate your test statistic.
T =
¯x − A
s/
√
n
Compare the test statistic and the critical value. Decide to
accept or reject the null hypothesis. Write a concluding
sentence.
Example
The National Association of Florists say the perfect
sunflower should be 90cm tall. We grow 8 sunflowers.
90 93 87 86 50 92 95 93
We want to see whether our sunflowers are too short at a
5% level of significance.
H0 : µ = 90.
H1 : µ < 90.
We are doing a 1-tailed test, our degrees of freedom is
8 − 1 = 7. Reading off our table we get a critical value of
−1.90.
The sample mean is 86 and the sample standard deviation
is 13.01. It follows the test statistic is −0.87.
The test statistic −0.87 is bigger than the critical value
−1.90 so we decide to accept the null hypothesis.
We conclude that our sunflowers are perfect.
The χ2
-test
The question will give you a table.
Write your null hypothesis H0 that the variables are
independent and your alternative hypothesis H1 that the
variables are dependent.
Read your critical value off the table.This will depend on
your significance level and the degrees of freedom of your
data (n − 1)(m − 1).
Calculate the row and column totals of the observed table.
Calculate the expected table. Row total times column total
divide by grand total.
Calculate the residual table. Observed minus expected.
Calculate the χ2 table. Residual value squared divided by
the expected value.
Calculate the test statistic. Add all the values in the χ2
table.
Compare the test statistic and the critical value. Decide to
accept or reject the null hypothesis. Write a concluding
sentence.
Example
The Institute for Studies want to know if the weather and
peoples happiness is independent to a 1% level of
significance. They collect the following data.
Happy Indifferent Sad
Rain 4 9 20
Snow 15 2 10
Sun 25 12 3
H0 : The weather and people’s happiness are independent.
H1 : People’s happiness depends on the weather.
Calculate the totals.
Happy Indifferent Sad Row total
Rain 4 9 20 33
Snow 15 2 10 27
Sun 25 12 3 40
Column total 44 23 33 100
Example
Calculate the expected table (to 3 d.p.).
14.52 7.59 10.89
11.88 6.21 8.91
17.6 9.2 13.2
Calculate the residual table (to 3 d.p.).
-10.52 1.41 9.11
3.12 -4.21 1.09
7.4 2.8 -10.2
Example
Calculate the χ2 table (to 3 d.p.).
7.623 0.262 7.621
0.819 2.854 0.133
3.111 0.8 7.882
The test statistic is 31.10 to 2 d.p.
The degree of freedom is (3 − 1) × (3 − 1) = 4. Our critical
value is 13.28.
Our test statistic is greater than our critical value so we
decide to reject our null hypothesis.
People’s happiness depends on the weather.
Standard Track Test B will be held during the
week beginning 21 April

More Related Content

What's hot

Measures of Variation
Measures of VariationMeasures of Variation
Measures of Variation
Rica Joy Pontilar
 
Measures of variation and dispersion report
Measures of variation and dispersion reportMeasures of variation and dispersion report
Measures of variation and dispersion reportAngelo
 
Chapter8
Chapter8Chapter8
Calculation of arithmetic mean
Calculation of arithmetic meanCalculation of arithmetic mean
Calculation of arithmetic mean
Sajina Nair
 
Gcse revision cards checked 190415
Gcse revision cards checked 190415Gcse revision cards checked 190415
Gcse revision cards checked 190415
claire meadows-smith
 
Properties of discrete probability distribution
Properties of discrete probability distributionProperties of discrete probability distribution
Properties of discrete probability distribution
JACKIE MACALINTAL
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendency
Raj Teotia
 
Chapter4
Chapter4Chapter4
Chapter4
Vu Vo
 
Chapter15
Chapter15Chapter15
Chapter15
Richard Ferreria
 
Converting normal to standard normal distribution and vice versa ppt
Converting normal to standard normal distribution and vice versa pptConverting normal to standard normal distribution and vice versa ppt
Converting normal to standard normal distribution and vice versa ppt
Ailz Lositaño
 
Statistics Formulae for School Students
Statistics Formulae for School StudentsStatistics Formulae for School Students
Statistics Formulae for School Students
dhatiraghu
 
Linear Rules
Linear RulesLinear Rules
Linear Rules
Passy World
 
1539 graphs linear equations and functions
1539 graphs linear equations and functions1539 graphs linear equations and functions
1539 graphs linear equations and functions
Dr Fereidoun Dejahang
 
Graphs linear equations and functions
Graphs linear equations and functionsGraphs linear equations and functions
Graphs linear equations and functions
anwarsalamappt
 
Hypothesis testing part iii for difference of means
Hypothesis testing part iii for difference of meansHypothesis testing part iii for difference of means
Hypothesis testing part iii for difference of means
Nadeem Uddin
 
Calculus ebook
Calculus ebookCalculus ebook
Calculus ebook
Allan Mabele Nambafu
 
The siegel-tukey-test-for-equal-variability
The siegel-tukey-test-for-equal-variabilityThe siegel-tukey-test-for-equal-variability
The siegel-tukey-test-for-equal-variability
Islamia College University Peshawar
 

What's hot (20)

Measures of Variation
Measures of VariationMeasures of Variation
Measures of Variation
 
Measures of variation and dispersion report
Measures of variation and dispersion reportMeasures of variation and dispersion report
Measures of variation and dispersion report
 
Es272 ch7
Es272 ch7Es272 ch7
Es272 ch7
 
Chapter8
Chapter8Chapter8
Chapter8
 
Calculation of arithmetic mean
Calculation of arithmetic meanCalculation of arithmetic mean
Calculation of arithmetic mean
 
Gcse revision cards checked 190415
Gcse revision cards checked 190415Gcse revision cards checked 190415
Gcse revision cards checked 190415
 
Properties of discrete probability distribution
Properties of discrete probability distributionProperties of discrete probability distribution
Properties of discrete probability distribution
 
Measures of central tendency
Measures of central tendencyMeasures of central tendency
Measures of central tendency
 
Chapter4
Chapter4Chapter4
Chapter4
 
Chapter15
Chapter15Chapter15
Chapter15
 
Converting normal to standard normal distribution and vice versa ppt
Converting normal to standard normal distribution and vice versa pptConverting normal to standard normal distribution and vice versa ppt
Converting normal to standard normal distribution and vice versa ppt
 
Slope intercept
Slope interceptSlope intercept
Slope intercept
 
Statistics Formulae for School Students
Statistics Formulae for School StudentsStatistics Formulae for School Students
Statistics Formulae for School Students
 
Linear Rules
Linear RulesLinear Rules
Linear Rules
 
1539 graphs linear equations and functions
1539 graphs linear equations and functions1539 graphs linear equations and functions
1539 graphs linear equations and functions
 
Statistics
StatisticsStatistics
Statistics
 
Graphs linear equations and functions
Graphs linear equations and functionsGraphs linear equations and functions
Graphs linear equations and functions
 
Hypothesis testing part iii for difference of means
Hypothesis testing part iii for difference of meansHypothesis testing part iii for difference of means
Hypothesis testing part iii for difference of means
 
Calculus ebook
Calculus ebookCalculus ebook
Calculus ebook
 
The siegel-tukey-test-for-equal-variability
The siegel-tukey-test-for-equal-variabilityThe siegel-tukey-test-for-equal-variability
The siegel-tukey-test-for-equal-variability
 

Similar to C2 st lecture 13 revision for test b handout

Normal Distribution, Binomial Distribution, Poisson Distribution
Normal Distribution, Binomial Distribution, Poisson DistributionNormal Distribution, Binomial Distribution, Poisson Distribution
Normal Distribution, Binomial Distribution, Poisson Distribution
Q Dauh Q Alam
 
Penggambaran Data Secara Numerik
Penggambaran Data Secara NumerikPenggambaran Data Secara Numerik
Penggambaran Data Secara Numerik
anom1392
 
Descriptive Statistics Formula Sheet Sample Populatio.docx
Descriptive Statistics Formula Sheet    Sample Populatio.docxDescriptive Statistics Formula Sheet    Sample Populatio.docx
Descriptive Statistics Formula Sheet Sample Populatio.docx
simonithomas47935
 
How normal distribution is used in heights, blood pressure, measurement error...
How normal distribution is used in heights, blood pressure, measurement error...How normal distribution is used in heights, blood pressure, measurement error...
How normal distribution is used in heights, blood pressure, measurement error...
Umair Raza
 
Key stage 3_mathematics_level_6_revision_
Key stage 3_mathematics_level_6_revision_Key stage 3_mathematics_level_6_revision_
Key stage 3_mathematics_level_6_revision_harlie90
 
Makalah ukuran penyebaran
Makalah ukuran penyebaranMakalah ukuran penyebaran
Makalah ukuran penyebaran
Nurkhalifah Anwar
 
Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or VarianceEstimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance
Long Beach City College
 
Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance
Long Beach City College
 
descriptive statistics.pptx
descriptive statistics.pptxdescriptive statistics.pptx
descriptive statistics.pptx
Teddyteddy53
 
Statistik 1 5 distribusi probabilitas diskrit
Statistik 1 5 distribusi probabilitas diskritStatistik 1 5 distribusi probabilitas diskrit
Statistik 1 5 distribusi probabilitas diskritSelvin Hadi
 
U unit8 ksb
U unit8 ksbU unit8 ksb
U unit8 ksb
Akhilesh Deshpande
 
analytical representation of data
 analytical representation of data analytical representation of data
analytical representation of data
Unsa Shakir
 
Fundamentals of Sampling Distribution and Data Descriptions
Fundamentals of Sampling Distribution and Data DescriptionsFundamentals of Sampling Distribution and Data Descriptions
Fundamentals of Sampling Distribution and Data Descriptions
Rajshahi University of Engineering & Technology(RUET), Bangladesh
 
10.Analysis of Variance.ppt
10.Analysis of Variance.ppt10.Analysis of Variance.ppt
10.Analysis of Variance.ppt
AbdulhaqAli
 
lecture8.ppt
lecture8.pptlecture8.ppt
lecture8.ppt
AlokKumar969617
 
Lecture8
Lecture8Lecture8
Lecture8
giftcertificate
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testing
ShaikhSaifullahKhali
 
lecture6.ppt
lecture6.pptlecture6.ppt
lecture6.ppt
Temporary57
 

Similar to C2 st lecture 13 revision for test b handout (20)

Normal Distribution, Binomial Distribution, Poisson Distribution
Normal Distribution, Binomial Distribution, Poisson DistributionNormal Distribution, Binomial Distribution, Poisson Distribution
Normal Distribution, Binomial Distribution, Poisson Distribution
 
Penggambaran Data Secara Numerik
Penggambaran Data Secara NumerikPenggambaran Data Secara Numerik
Penggambaran Data Secara Numerik
 
Descriptive Statistics Formula Sheet Sample Populatio.docx
Descriptive Statistics Formula Sheet    Sample Populatio.docxDescriptive Statistics Formula Sheet    Sample Populatio.docx
Descriptive Statistics Formula Sheet Sample Populatio.docx
 
How normal distribution is used in heights, blood pressure, measurement error...
How normal distribution is used in heights, blood pressure, measurement error...How normal distribution is used in heights, blood pressure, measurement error...
How normal distribution is used in heights, blood pressure, measurement error...
 
Key stage 3_mathematics_level_6_revision_
Key stage 3_mathematics_level_6_revision_Key stage 3_mathematics_level_6_revision_
Key stage 3_mathematics_level_6_revision_
 
Statistics 1 revision notes
Statistics 1 revision notesStatistics 1 revision notes
Statistics 1 revision notes
 
Makalah ukuran penyebaran
Makalah ukuran penyebaranMakalah ukuran penyebaran
Makalah ukuran penyebaran
 
Normal Distribution
Normal DistributionNormal Distribution
Normal Distribution
 
Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or VarianceEstimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance
 
Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance Estimating a Population Standard Deviation or Variance
Estimating a Population Standard Deviation or Variance
 
descriptive statistics.pptx
descriptive statistics.pptxdescriptive statistics.pptx
descriptive statistics.pptx
 
Statistik 1 5 distribusi probabilitas diskrit
Statistik 1 5 distribusi probabilitas diskritStatistik 1 5 distribusi probabilitas diskrit
Statistik 1 5 distribusi probabilitas diskrit
 
U unit8 ksb
U unit8 ksbU unit8 ksb
U unit8 ksb
 
analytical representation of data
 analytical representation of data analytical representation of data
analytical representation of data
 
Fundamentals of Sampling Distribution and Data Descriptions
Fundamentals of Sampling Distribution and Data DescriptionsFundamentals of Sampling Distribution and Data Descriptions
Fundamentals of Sampling Distribution and Data Descriptions
 
10.Analysis of Variance.ppt
10.Analysis of Variance.ppt10.Analysis of Variance.ppt
10.Analysis of Variance.ppt
 
lecture8.ppt
lecture8.pptlecture8.ppt
lecture8.ppt
 
Lecture8
Lecture8Lecture8
Lecture8
 
Hypothesis testing
Hypothesis testingHypothesis testing
Hypothesis testing
 
lecture6.ppt
lecture6.pptlecture6.ppt
lecture6.ppt
 

More from fatima d

10 terrorism
10 terrorism10 terrorism
10 terrorismfatima d
 
09 non governmental organisations
09  non governmental organisations09  non governmental organisations
09 non governmental organisationsfatima d
 
17 china and the developing world
17 china and the developing world17 china and the developing world
17 china and the developing worldfatima d
 
16 development assistance
16 development assistance16 development assistance
16 development assistancefatima d
 
15 development issues
15 development issues15 development issues
15 development issuesfatima d
 
12b beyond unipolarity
12b beyond unipolarity12b beyond unipolarity
12b beyond unipolarityfatima d
 
12a beyond bipolarity fukuyama and huntington
12a  beyond bipolarity   fukuyama and huntington12a  beyond bipolarity   fukuyama and huntington
12a beyond bipolarity fukuyama and huntingtonfatima d
 
Un covenant economioc social cultural
Un covenant economioc social culturalUn covenant economioc social cultural
Un covenant economioc social culturalfatima d
 
Un covenant civil political rights
Un covenant civil political rightsUn covenant civil political rights
Un covenant civil political rightsfatima d
 
Cairo declaration 1990
Cairo declaration 1990Cairo declaration 1990
Cairo declaration 1990fatima d
 
Un declaration of human rights
Un declaration of human rightsUn declaration of human rights
Un declaration of human rightsfatima d
 
C2 st lecture 6 handout
C2 st lecture 6 handoutC2 st lecture 6 handout
C2 st lecture 6 handoutfatima d
 
C2 st lecture 4 handout
C2 st lecture 4 handoutC2 st lecture 4 handout
C2 st lecture 4 handoutfatima d
 
C2 st lecture 3 handout
C2 st lecture 3 handoutC2 st lecture 3 handout
C2 st lecture 3 handoutfatima d
 
C2 st lecture 8 pythagoras and trigonometry handout
C2 st lecture 8   pythagoras and trigonometry handoutC2 st lecture 8   pythagoras and trigonometry handout
C2 st lecture 8 pythagoras and trigonometry handoutfatima d
 
C2 st lecture 11 the t-test handout
C2 st lecture 11   the t-test handoutC2 st lecture 11   the t-test handout
C2 st lecture 11 the t-test handoutfatima d
 
Foundation c2 exam june 2013 resit 2 sols
Foundation c2 exam june 2013 resit 2 solsFoundation c2 exam june 2013 resit 2 sols
Foundation c2 exam june 2013 resit 2 solsfatima d
 
Foundation c2 exam may 2013 sols
Foundation c2 exam may 2013 solsFoundation c2 exam may 2013 sols
Foundation c2 exam may 2013 solsfatima d
 
Foundation c2 exam june 2013 resit sols
Foundation c2 exam june 2013 resit solsFoundation c2 exam june 2013 resit sols
Foundation c2 exam june 2013 resit solsfatima d
 
Ft test b jan 2012 sols
Ft test b jan 2012 solsFt test b jan 2012 sols
Ft test b jan 2012 solsfatima d
 

More from fatima d (20)

10 terrorism
10 terrorism10 terrorism
10 terrorism
 
09 non governmental organisations
09  non governmental organisations09  non governmental organisations
09 non governmental organisations
 
17 china and the developing world
17 china and the developing world17 china and the developing world
17 china and the developing world
 
16 development assistance
16 development assistance16 development assistance
16 development assistance
 
15 development issues
15 development issues15 development issues
15 development issues
 
12b beyond unipolarity
12b beyond unipolarity12b beyond unipolarity
12b beyond unipolarity
 
12a beyond bipolarity fukuyama and huntington
12a  beyond bipolarity   fukuyama and huntington12a  beyond bipolarity   fukuyama and huntington
12a beyond bipolarity fukuyama and huntington
 
Un covenant economioc social cultural
Un covenant economioc social culturalUn covenant economioc social cultural
Un covenant economioc social cultural
 
Un covenant civil political rights
Un covenant civil political rightsUn covenant civil political rights
Un covenant civil political rights
 
Cairo declaration 1990
Cairo declaration 1990Cairo declaration 1990
Cairo declaration 1990
 
Un declaration of human rights
Un declaration of human rightsUn declaration of human rights
Un declaration of human rights
 
C2 st lecture 6 handout
C2 st lecture 6 handoutC2 st lecture 6 handout
C2 st lecture 6 handout
 
C2 st lecture 4 handout
C2 st lecture 4 handoutC2 st lecture 4 handout
C2 st lecture 4 handout
 
C2 st lecture 3 handout
C2 st lecture 3 handoutC2 st lecture 3 handout
C2 st lecture 3 handout
 
C2 st lecture 8 pythagoras and trigonometry handout
C2 st lecture 8   pythagoras and trigonometry handoutC2 st lecture 8   pythagoras and trigonometry handout
C2 st lecture 8 pythagoras and trigonometry handout
 
C2 st lecture 11 the t-test handout
C2 st lecture 11   the t-test handoutC2 st lecture 11   the t-test handout
C2 st lecture 11 the t-test handout
 
Foundation c2 exam june 2013 resit 2 sols
Foundation c2 exam june 2013 resit 2 solsFoundation c2 exam june 2013 resit 2 sols
Foundation c2 exam june 2013 resit 2 sols
 
Foundation c2 exam may 2013 sols
Foundation c2 exam may 2013 solsFoundation c2 exam may 2013 sols
Foundation c2 exam may 2013 sols
 
Foundation c2 exam june 2013 resit sols
Foundation c2 exam june 2013 resit solsFoundation c2 exam june 2013 resit sols
Foundation c2 exam june 2013 resit sols
 
Ft test b jan 2012 sols
Ft test b jan 2012 solsFt test b jan 2012 sols
Ft test b jan 2012 sols
 

Recently uploaded

Unit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdfUnit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdf
Thiyagu K
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
MysoreMuleSoftMeetup
 
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER  FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...TESDA TM1 REVIEWER  FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
EugeneSaldivar
 
The geography of Taylor Swift - some ideas
The geography of Taylor Swift - some ideasThe geography of Taylor Swift - some ideas
The geography of Taylor Swift - some ideas
GeoBlogs
 
Additional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdfAdditional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdf
joachimlavalley1
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
Celine George
 
Polish students' mobility in the Czech Republic
Polish students' mobility in the Czech RepublicPolish students' mobility in the Czech Republic
Polish students' mobility in the Czech Republic
Anna Sz.
 
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXXPhrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
MIRIAMSALINAS13
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
Thiyagu K
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
Pavel ( NSTU)
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
Tamralipta Mahavidyalaya
 
Template Jadual Bertugas Kelas (Boleh Edit)
Template Jadual Bertugas Kelas (Boleh Edit)Template Jadual Bertugas Kelas (Boleh Edit)
Template Jadual Bertugas Kelas (Boleh Edit)
rosedainty
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
beazzy04
 
Basic phrases for greeting and assisting costumers
Basic phrases for greeting and assisting costumersBasic phrases for greeting and assisting costumers
Basic phrases for greeting and assisting costumers
PedroFerreira53928
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
kaushalkr1407
 
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup   New Member Orientation and Q&A (May 2024).pdfWelcome to TechSoup   New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
TechSoup
 
The French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free downloadThe French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free download
Vivekanand Anglo Vedic Academy
 
Introduction to Quality Improvement Essentials
Introduction to Quality Improvement EssentialsIntroduction to Quality Improvement Essentials
Introduction to Quality Improvement Essentials
Excellence Foundation for South Sudan
 
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
siemaillard
 
The Art Pastor's Guide to Sabbath | Steve Thomason
The Art Pastor's Guide to Sabbath | Steve ThomasonThe Art Pastor's Guide to Sabbath | Steve Thomason
The Art Pastor's Guide to Sabbath | Steve Thomason
Steve Thomason
 

Recently uploaded (20)

Unit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdfUnit 2- Research Aptitude (UGC NET Paper I).pdf
Unit 2- Research Aptitude (UGC NET Paper I).pdf
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
 
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER  FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...TESDA TM1 REVIEWER  FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
 
The geography of Taylor Swift - some ideas
The geography of Taylor Swift - some ideasThe geography of Taylor Swift - some ideas
The geography of Taylor Swift - some ideas
 
Additional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdfAdditional Benefits for Employee Website.pdf
Additional Benefits for Employee Website.pdf
 
How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17How to Make a Field invisible in Odoo 17
How to Make a Field invisible in Odoo 17
 
Polish students' mobility in the Czech Republic
Polish students' mobility in the Czech RepublicPolish students' mobility in the Czech Republic
Polish students' mobility in the Czech Republic
 
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXXPhrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
 
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdfUnit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
 
Home assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdfHome assignment II on Spectroscopy 2024 Answers.pdf
Home assignment II on Spectroscopy 2024 Answers.pdf
 
Template Jadual Bertugas Kelas (Boleh Edit)
Template Jadual Bertugas Kelas (Boleh Edit)Template Jadual Bertugas Kelas (Boleh Edit)
Template Jadual Bertugas Kelas (Boleh Edit)
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
 
Basic phrases for greeting and assisting costumers
Basic phrases for greeting and assisting costumersBasic phrases for greeting and assisting costumers
Basic phrases for greeting and assisting costumers
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
 
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup   New Member Orientation and Q&A (May 2024).pdfWelcome to TechSoup   New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
 
The French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free downloadThe French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free download
 
Introduction to Quality Improvement Essentials
Introduction to Quality Improvement EssentialsIntroduction to Quality Improvement Essentials
Introduction to Quality Improvement Essentials
 
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
 
The Art Pastor's Guide to Sabbath | Steve Thomason
The Art Pastor's Guide to Sabbath | Steve ThomasonThe Art Pastor's Guide to Sabbath | Steve Thomason
The Art Pastor's Guide to Sabbath | Steve Thomason
 

C2 st lecture 13 revision for test b handout

  • 1. Lecture 13 - Revision for Test B C2 Foundation Mathematics (Standard Track) Dr Linda Stringer Dr Simon Craik l.stringer@uea.ac.uk s.craik@uea.ac.uk INTO City/UEA London
  • 2. Outline Lecture 8 Pythagoras’ Theorem and Trigonometry Sine and Cosine rules, Areas Lecture 9 Probability Lecture 10 Mode, Median and Interquartile range Mean, Absolute deviation, Standard deviation Z-test Lecture 11 T-test Lecture 12 χ2 -test
  • 3. Pythagoras’ Theorem Only works in right-angled triangles. a b c a2 + b2 = hyp2
  • 4. sin, cos and tan ratios Only works in right-angled triangles. opp adj hyp A tan(A) = opp adj cos(A) = adj hyp sin(A) = opp hyp
  • 5. Angle rule Works in any triangle. a bc B C A A + B + C = 180
  • 6. Sine rule Works in any triangle. a bc B C A a sin A = b sin B = c sin C
  • 7. Cosine rule Works in any triangle. a bc B C A a2 = b2 + c2 − 2bc cos(A)
  • 8. Area Works in any triangle. a bc B C A Area = 1 2 ab sin(C)
  • 9. Probability The sum of all probabilities is 1. The probability an event A happens is denoted P(A) and is a number between 0 and 1. The probability A does not happen is 1 − P(A). The probability A and B happens is P(A) × P(B). The probability A or B happens is P(A) + P(B).
  • 10. Probability trees You can use a probability tree when there is more than one event. Draw different tiers of branches for different events, and write the probability next to the branch. Multiply probabilities along the branches (AND) Add up the probabilities at the end of each branch (OR) The total of all the probabilities at the end of the branches should be 1 The probabilities for the second tier may be the same as for the first tier, or they may be different
  • 11. Probability tree - roll a fair die twice (or roll two fair dice) What is the probability that I roll two fours? What is the probability that I roll no fours? What is the probability that I roll exactly one four? What is the probability that I roll at least one four? First roll Second roll P(4, 4) = 1 6 × 1 6 = 1 36 P(4, ¬4) = 1 6 × 5 6 = 5 36 P(¬4, 4) = 5 6 × 1 6 = 5 36 P(¬4, ¬4) = 5 6 × 5 6 = 25 36 ¬4 ¬4 5/6 41/6 5/6 4 ¬4 5/6 41/6 1/6
  • 12. Mode The mode is the most frequent object in your data. X = 5 8 -3 7 8 2 8 The mode of X is 8. Y = 0 2 1 6 5 1 2 3 The modes of Y are 1 and 2.
  • 13. Median The median is the middle data. X = 5 8 -3 7 8 2 8 Order the data X = -3 2 5 7 8 8 8 7 × 1/2 = 3.5 Round up to 4. The median of X is the fourth term 7.
  • 14. Median Y = 0 2 1 6 5 1 2 3 Order the data Y = 0 1 1 2 2 3 5 6 8 × 1/2 = 4 Add the fourth term and the fifth term and divide by 2. The median of Y is 2+2 2 = 2.
  • 15. Interquartile range First order the data, with values increasing from left to right. We want to find two values: the first quartile Q1 and the third quartile Q3. Let n be the size of the data set (the number of values). To find Q1 we multiply n by 1 4 . If n 4 is an integer (whole number) then Q1 is the midpoint of the (n 4 )th value and the (n 4 + 1)th value If n 4 is not an integer then round it up to the nearest integer. Q1 is the corresponding value. To find Q3 we multiply n by 3 4 . If 3n 4 is an integer then Q3 is the midpoint of the (3n 4 )th value and the (3n 4 + 1)th value If 3n 4 is not an integer then round it up to the nearest integer. Q3 is the corresponding value. The interquartile range is Q3 − Q1.
  • 16. Interquartile range The interquartile range is the middle half of the data. Take the ordered data X = -3 2 5 7 8 8 8 Find Q1 : 7 × 1/4 = 1.75 Round up to 2. The first quartile if X is the second term, Q1 = 2. Find Q3 : 7 × 3/4 = 5.25 Round up to 6. The third quartile if X is the sixth term, Q3 = 8. The interquartile range is Q3 − Q1 = 8 − 2 = 6
  • 17. Interquartile range The interquartile range is the middle half of the data. Take the ordered data Y = 0 1 1 2 2 3 5 6 Find Q1 : 8 × 1/4 = 2 Add the second term and the third term and divide by 2. The first quartile of X is Q1 = 1+1 2 = 1. Find Q3 : 8 × 3/4 = 6 Add the sixth term and the seventh term and divide by 2. The third quartile of X is Q3 = 3+5 2 = 4. The interquartile range is Q3 − Q1 = 4 − 1 = 3
  • 18. Mean The mean is the average of the data. ¯x = x n 5 8 -3 7 8 2 8 ¯x = 5 + 8 + (−3) + 7 + 8 + 2 + 8 7 = 35 7 = 5
  • 19. Absolute deviation The absolute deviation is the average distance of the data from the mean. AD = |x − ¯x| n 5 8 -3 7 8 2 8 Calculate |x − ¯x| (remember that we calculated ¯x = 5) 0 3 8 2 3 3 3 Add these values together and divide by the number of values in the list AD = 0 + 3 + 8 + 2 + 3 + 3 + 3 7 = 22 7
  • 20. Standard deviation 5 8 -3 7 8 2 8 The standard deviation, σ, is a measure of spread. First find the variance, σ2. σ2 = x2 n − ¯x2 Calculate x2: 25 64 9 49 64 4 64 Add these values together, divide by the size of the data and subtract the mean squared. σ2 = 279 7 − 52 = 104 7 The standard deviation is the square root of the variance σ = 3.85 to 2 d.p.
  • 21. Structure of hypothesis tests The Z-test, the T-test and the χ2-test all have the same structure Hypotheses (H0 and H1) Critical value (look it up in a table, and for the Z-test and T-test add a sketch showing rejection regions ) Test statistic (calculate) Decision (accept/reject H0) Conclusion (write a sentence)
  • 22. The Z-test The question will tell you the population mean µ and the standard deviation of the population σ. It may also give you information for your alternative hypothesis. Write your null hypothesis H0 and your alternative hypothesis H1. Read your critical value off the table.This will depend on your significance level and your alternative hypothesis. You will be given a sample mean ¯x and the size of the sample data n. Calculate your test statistic. Z = ¯x − A σ/ √ n Compare the test statistic and the critical value. Decide to accept or reject the null hypothesis. Write a concluding sentence.
  • 23. Example The National Association of Florists say the perfect sunflower should be 90cm tall with a standard deviation of 9.5cm. We grow 100 sunflowers with a mean height of 92 cm. We want to see whether or not our sunflowers are perfect to a 5% level of significance. H0 : µ = 90. H1 : µ = 90. We are doing a 2-tailed test. Reading off our table we get critical values of −1.96 and 1.96. The test statistic is 92−90 9.5/ √ 100 = 2.11 to 2 d.p. The test statistic 2.11 is bigger than the critical value 1.96 so we decide to reject the null hypothesis. We conclude that our sunflowers are not perfect.
  • 24. The T-test The question will tell you the population mean µ. It will also give you a small table of size n with some data. It may also give you information for your alternative hypothesis. Write your null hypothesis H0 and your alternative hypothesis H1. Read your critical value off the table.This will depend on your significance level, your alternative hypothesis and the degree of freedom of your data. You will calculate the sample mean ¯x and the sample standard deviation s. Calculate your test statistic. T = ¯x − A s/ √ n Compare the test statistic and the critical value. Decide to accept or reject the null hypothesis. Write a concluding sentence.
  • 25. Example The National Association of Florists say the perfect sunflower should be 90cm tall. We grow 8 sunflowers. 90 93 87 86 50 92 95 93 We want to see whether our sunflowers are too short at a 5% level of significance. H0 : µ = 90. H1 : µ < 90. We are doing a 1-tailed test, our degrees of freedom is 8 − 1 = 7. Reading off our table we get a critical value of −1.90. The sample mean is 86 and the sample standard deviation is 13.01. It follows the test statistic is −0.87. The test statistic −0.87 is bigger than the critical value −1.90 so we decide to accept the null hypothesis. We conclude that our sunflowers are perfect.
  • 26. The χ2 -test The question will give you a table. Write your null hypothesis H0 that the variables are independent and your alternative hypothesis H1 that the variables are dependent. Read your critical value off the table.This will depend on your significance level and the degrees of freedom of your data (n − 1)(m − 1). Calculate the row and column totals of the observed table. Calculate the expected table. Row total times column total divide by grand total. Calculate the residual table. Observed minus expected. Calculate the χ2 table. Residual value squared divided by the expected value. Calculate the test statistic. Add all the values in the χ2 table. Compare the test statistic and the critical value. Decide to accept or reject the null hypothesis. Write a concluding sentence.
  • 27. Example The Institute for Studies want to know if the weather and peoples happiness is independent to a 1% level of significance. They collect the following data. Happy Indifferent Sad Rain 4 9 20 Snow 15 2 10 Sun 25 12 3 H0 : The weather and people’s happiness are independent. H1 : People’s happiness depends on the weather. Calculate the totals. Happy Indifferent Sad Row total Rain 4 9 20 33 Snow 15 2 10 27 Sun 25 12 3 40 Column total 44 23 33 100
  • 28. Example Calculate the expected table (to 3 d.p.). 14.52 7.59 10.89 11.88 6.21 8.91 17.6 9.2 13.2 Calculate the residual table (to 3 d.p.). -10.52 1.41 9.11 3.12 -4.21 1.09 7.4 2.8 -10.2
  • 29. Example Calculate the χ2 table (to 3 d.p.). 7.623 0.262 7.621 0.819 2.854 0.133 3.111 0.8 7.882 The test statistic is 31.10 to 2 d.p. The degree of freedom is (3 − 1) × (3 − 1) = 4. Our critical value is 13.28. Our test statistic is greater than our critical value so we decide to reject our null hypothesis. People’s happiness depends on the weather.
  • 30. Standard Track Test B will be held during the week beginning 21 April