Sabah Science Secondary Schoo1 (2)

7/27/2019 Sabah Science Secondary Schoo1 (2)

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SABAH SCIENCE SECONDARY

SCHOOL

(HIGH PERFORMING SCHOOL)

Statistic Of 5Delta Addmaths

Marks

NAME:NURUL AINA SHAZWANA

CLASS:5D

I/C NUMBER:961007-12-5870

TEACHER:MADAM CHIN SIAU

LING


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CONTENT

ACKNOWLEDGEMENT

OBJECTIVE

INTRODUCTION

TASK SPECIFICATION

PROBLEM SOLVING

FUTHER EXPLORATION

REFLECTION


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ACKNOWLEDGEMENT

Grace be upon to Allah, with his blessing, I can finished my Additoinal

Mathematics Project Work. Of course, it was kind of hard work but the

project was interesting. I have learned a lot from this project besides having a

chance to enchance my computer skill. Nevertheless, all of this would not have

been possible without any support from everyone.

Firstly, I would like to say thank to God with all my heart for helping me

to finish my project within the time limit. Thank to God for blessing me with a

clear understanding of this project, dedicated teachers, helpful parents and the

plentiful resources available to me. Of course, they are just too many blessing

that I were to mention them all, the list would never be end.

The most important person is none other than my addmaths

teacher,Madam Chin Siau Ling. She always strive to give us the best. The next

person who played major role in helping me to complete my project is my

parents, they have been very helpful and extremely supportive of me. I would

like also to thank to both of my parents for the financial support they have

given to me.

Last but not least, I would like to thank to all my friends, especially to my

closer friends for giving and sharing information with me. Thank you.


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OBJECTIVES

-The aim of carrying this project work are :-

1. To develop mathematical knowledge in a way which increase students

interest and confidence.

2. To apply mathematics to everyday situations and to begin to understand the

part that mathematics plays in the world in which we live.

3. To improve thinking skill and promote effective mathematical

communication.

4. To assist student to develop positive attitude and personalities,intrinsic

mathematical values such as accurancy,confidence and system reasoning.

5. To stimulate learning and enhance effective learning.


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INTRODUCTION

The History of statistics can be said to start around 1749 although, over time,

there have been changes to the interpretation of the word statistics. In early

times, the meaning was restricted to information about states. This was later

extended to include all collections of information of all types, and later still it

was extended to include the analysis and interpretation of such data. In modern

terms, "statistics" means both sets of collected information, as in national

accounts and temperature records, and analytical work which requires

statistical inference.

Statistical activities are often associated with models expressed using

probabilities, and require probability theory for them to be put on a firm

theoretical basis: see History of probability.

A number of statistical concepts have had an important impact on a wide range

of sciences. These include the design of experiments and approaches to

statistical inference such as Bayesian inference, each of which can be

considered to have their own sequence in the development of the ideas

underlying modern statistics.

Analysis of data is a process of inspecting, cleaning, transforming, and modeling

data with the goal of highlighting useful information, suggesting conclusions, and

supporting decision making. Data analysis has multiple facts and approaches,

encompassing diverse techniques under a variety of names, in different

business, science, and social science domains.


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Data analysis is a process used to transform, remodel and revise certain

information (data) with a view to reach to a certain conclusion for a given

situation or problem. Data analysis can be done by different methods as

according to the needs and requirements. For example if a school principal wants

to know whether there is a relationship between students performance on the

district writing assessment and their socioeconomic levels. In other words, do

students who come from lower socioeconomic backgrounds perform lower, as we

are led to believe? Or are there other variables responsible for the variance in

writing performance? Again, a simple correlation analysis will help describe the

students performance and help explain the relationship between the issues of

performance and socioeconomic level.

Analysis does not have to involve complex statistics. Data analysis in schools

involves collecting data and using that data to improve teaching and learning.

Interestingly, principals and teachers have it pretty easy. In most cases, the

collection of data has already been done. Schools regularly collect attendance

data, transcript records, discipline referrals, quarterly or semester grades,

norm- and criterion-referenced test scores, and a variety of other useful data.

Rather than complex statistical formulas and tests, it is generally simple counts,

averages, percents, and rates that educators are interested in.


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PART 1

(IMPORTANCE OF DATA IN DAILY LIFE)

Data plays an important role in the information we receive on a daily basis from

environmental print, newspapers, television, magazines, the Internet, etc. Other

areas of mathematics are deeply embedded into this strand of the curriculum.

When working through data analysis activities, students naturally draw upon

other mathematical skills such as understanding of number, operations,

patterning, and various problem solving strategies. Students view various forms

of data in many other areas of the curriculum, such as prediction charts in

Science,population graphs in Social Studies, or informational text in

LanguageArts. For students, the process of data analysis is not only interesting,

but constitutes real problem solving linked to many aspects of theirenvironment.

There are many benefits of data analysis however; the most important ones are

as follows: - data analysis helps in structuring the findings from different

sources of data collection like survey research. It is again very helpful in

breaking a macro problem into micro parts. Data analysis acts like a filter when

it comes to acquiring meaningful insights out of huge data-set. Every researcher

has sort out huge pile of data that he/she has collected, before reaching to a

conclusion of the research question. Mere data collection is of no use to the

researcher. Data analysis proves to be crucial in this process. It provides ameaningful base to critical decisions. It helps to create a complete dissertation

proposal.

One of the most important uses of data analysis is that it helps in keeping

human bias away from research conclusion with the help of proper statistical

treatment. With the help of data analysis a researcher can filter both

qualitative and quantitative data for anassignment writing projects. Thus, it can


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be said that data analysis is of utmost importance for both the research and

the researcher. Or to put it in another words data analysis is as important to a

researcher as it is important for a doctor to diagnose the problem of the

patient before giving him any treatment.

In business,data analysis is important to businesses will be an understatement.

In fact, no business can survive without analyzing available data. Visualize the

following situations like a pharma company is performing trials on number of

patients to test its new drug to fight cancer, number of patients under the trial

is well over 500, A company wants to launch new variant of its existing line offruit juice. It wants to carry out the survey analysis and arrive at some

meaningful conclusion. Sales director of a company knows that there is

something wrong with one of its successful products, however hasn't yet

carried out any market research data analysis. How and what does he conclude?

These situations are indicative enough to conclude that data analysis is the

lifeline of any business. Whether one wants to arrive at some marketing

decisions or fine-tune new product launch strategy, data analysis is the key to

all the problems.

What is the importance of data analysis - instead, one should say what is not

important about data analysis.

Merely analyzing data isn't sufficient from the point of view of making a

decision. How does one interpret from the analyzed data is more important.

Thus, data analysis is not a decision making system, but decision supporting

system.

Data analysis can offer the following benefits such as structuring the findings

from survey research or other means of data collection,break a macro picture

into a micro one,Acquiring meaningful insights from the dataset


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basing critical decisions from the findings and Ruling out human bias through

proper statistical treatment.


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1. Types of Measure of Central Tendency and of Measure of DispersionCentral tendency gets at the typical score on the variable, while dispersion gets at how

much variety there is in the scores. When describing the scores on a single variable, it is

customary to report on both the central tendency and the dispersion. Not all measures of

central tendency and not all measures of dispersion can be used to describe the values of

cases on every variable. What choices you have depend on the variables level of

measurement.

Mean

The mean is what in everyday conversation is called the average. It is calculated by simply

adding the values of all the valid cases together and dividing by the number of valid cases.

Or The mean is an interval/ratio measure of central tendency. Its calculation requires that the

attributes of the variable represent a numeric scale

Mode

The mode is the attribute of a variable that occurs most often in the data set.

For ungroup data, we can find mode by finding the modal class and draw the modal class and

two classes adjacent to the modal class. Two lines from the adjacent we crossed to find the

intersection. The intersection value is known as the mode.

Median


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The median is a measure of central tendency. It identifies the value of the middle case when

the cases have been placed in order or in line from low to high. The middle of the line is as

far from being extreme as you can get.

There are as many cases in line in front of the middle case as behind the middle case. The

median is the attribute used by that middle case. When you know the value of the median,

you know that at least half the cases had that value or a higher value, while at least half the

cases had that value or a lower value.

Range

The distance between the minimum and the maximum is called the range. The larger the

value of the range, the more dispersed the cases are on the variable; the smaller the value of

the range, the less dispersed (the more concentrated) the cases are on the variable

Range = maximum valueminimum value

Interquartile range is the distance between the 75th percentile and the 25th percentile. The

IQR is essentially the range of the middle 50% of the data. Because it uses the middle 50%,

the IQR is not affected by outliers or extreme values.

( ) ( )

Interquartile range = Q3 - Q1

Standard Deviation

The standard deviation tells you the approximate average distance of cases from the mean.

This is easier to comprehend than the squared distance of cases from the mean. The standarddeviation is directly related to the variance.


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If you know the value of the variance, you can easily figure out the value of the standard

deviation. The reverse is also true. If you know the value of the standard deviation, you can

easily calculate the value of the variance. The standard deviation is the square root of the

variance

( )


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1. the Mark Additional Mathematics test scores for your class

Student Marks

1 89

2 86

3 79

4 77

5 71

6 69

7 69

8 68

9 67

10 66

11 65

12 60

13 59

14 57

15 52

16 49

17 47

18 47

19 45

20 43

21 39

22 37

23 35


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24 31

25 29

26 27

27 26

28 22

29 19

30 15

MARKS TALLY FREQUENCY

0-10 0

11-20 2

21-30 4

31-40 4

41-50 5

51-60 3

61-70 7

71-80 3

81-90 2

91-100 0


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1)a)Mean

MARKS MIDPOINT,x FREQUENCY,f Fx

1-10 5.5 0 0

11-20 15.5 2 31

21-30 25.5 4 102

31-40 35.5 4 142

41-50 45.5 5 227.5

51-60 55.5 3 166.5

61-70 65.5 7 458.5

71-80 75.5 3 226.5

81-90 85.5 2 171

91-100 95.5 0 0

TOTAL 30 1525

f = 30

fx = 1525

Mean,

=

=50.8333


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(2) mode

The modal class is 61-70, the majority of the students got that marks.

To find the mode mark, we draw the modal class and two classes adjacent to themodal class.

(REFER TO HISTOGRAM 1)

Based on the histogram;

Mode = 64.5


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Reflection

http://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-

in-research.html
http://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-in-research.htmlhttp://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-in-research.htmlhttp://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-in-research.htmlhttp://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-in-research.htmlhttp://dissertation-help-uk.blogspot.com/2011/12/importance-of-data-analysis-in-research.html

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Sabah Science Secondary Schoo1 (2)