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Tuesday, August 2, 2011

STATISTIK - MTE 3105




PENGENALAN

Kursus ini diambil oleh pelajar PISMP Sem 03 Pengajian Matematik Rendah di semua IPG di Malaysia


Antara kandungan tajuk yang dipelajari adalah seperti :
1.0 Kebarangkalian
2.0 Teori Persampelan
3.0 Teori Anggaran
4.0 Linear Progression
5.0 Chi-square - Ujian Hipotesis
6.0 Analisis Varians (ANOVA)
7.0 Ujian Hipotesis - ujian -t


O    Contoh Latihan 1 (Ujian Hipotesis)
        Uji samada taburan kekerapan diberi di dalam jadual di bawah adalah satu sampel daripada satu populasi normal.
Nilai (x)
7.0
8.0
9.0
10.0
11.0
Kekerapan kelas (f)
11
33
77
63
16

O  Contoh 2 :(Khi-kuasadua)
Sebuah dadu dilambung 240 kali dan keputusan-keputusan adalah seperti berikut:

Nilai muka dadu, x
1
2
3
4
5
6
Kekerapaan, f
50
35
44
32
30
49
OJalankan satu ujian khi - kuasadua bagi kebaikan pemadanan untuk menentukan sama ada dadu tidak terpincang pada aras keertian 1%.

12 comments:

  1. kenapa x disediakan link nota seklai...???
    leh gak er...

    ReplyDelete
  2. Masih dalam pengemaskinian bahan sumber rujukan . terima kasih atas saranan anda ....:)

    ReplyDelete
  3. Teorem Persampelan Mudah
    1. Nota Taburan Persampelan : http://www.econ.upm.edu.my/~alias/MGM3162/BAB...
    2. http://www.ukm.my/ppsmfst/STQS1123.htm

    ReplyDelete
  4. Types of Sampling
    We may then consider different types of probability samples. Although there are a number of different methods that might be used to create a sample, they generally can be grouped into one of two categories:probability samples or non-probability samples.
    Probability Samples
    The idea behind this type is random selection. More specifically, each sample from the population of interest has a known probability of selection under a given sampling scheme. There are four categories of probability samples described below.
    Simple Random Sampling
    The most widely known type of a random sample is the simple random sample (SRS). This is characterized by the fact that the probability of selection is the same for every case in the population. Simple random sampling is a method of selecting n units from a population of size N such that every possible sample of size an has equal chance of being drawn.
    An example may make this easier to understand. Imagine you want to carry out a survey of 100 voters in a small town with a population of 1,000 eligible voters. With a town this size, there are "old-fashioned" ways to draw a sample. For example, we could write the names of all voters on a piece of paper, put all pieces of paper into a box and draw 100 tickets at random. You shake the box, draw a piece of paper and set it aside, shake again, draw another, set it aside, etc. until we had 100 slips of paper. These 100 form our sample. And this sample would be drawn through a simple random sampling procedure - at each draw, every name in the box had the same probability of being chosen.
    In real-world social research, designs that employ simple random sampling are difficult to come by. We can imagine some situations where it might be possible - you want to interview a sample of doctors in a hospital about work conditions. So you get a list of all the physicians that work in the hospital, write their names on a piece of paper, put those pieces of paper in the box, shake and draw. But in most real-world instances it is impossible to list everything on a piece of paper and put it in a box, then randomly draw numbers until desired sample size is reached.
    There are many reasons why one would choose a different type of probability sample in practice.

    ReplyDelete
  5. Sample Exercises 01(Try to solve this problems)

    Let's suppose your sampling frame is a large city's telephone book that has 2,000,000 entries. To take aSRS, you need to associate each entry with a number and choose n= 200 numbers from N= 2,000,000. This could be quite an ordeal. Instead, you decide to take a random start between 1 and N/n= 20,000 and then take every 20,000th name, etc. This is an example of systematic sampling, a technique discussed more fully below.

    ReplyDelete
  6. Important notes on Sampling Method

    A survey is carried out at a university to estimate the percentage of undergraduates living at home during the current semester. The university's registrar keeps an alphabetical list of all undergraduates, with their current addresses. Suppose there are 10,000 undergraduates registered in the semester during which this research is conducted. Someone proposes to choose a number at random between one and one hundred, count that far down the list, then take that name and every hundredth name after it for the 
    sample.
    a. What will the sample size be?
    b. Is this a probability method? Is it the same as simple random sampling
    c. Assume now that the registrar's list is not alphabetical, but rather ordered by GPA (from low to high). Would this method of sampling be adequate?

    Someone else proposes to go out and take the first hundred undergraduates she sees as the sample.
    d. Is this a probability method? Is it the same as simple random sampling?

    ReplyDelete
  7. Ujian hipotesis
    http://www.youtube.com/watch?v=abjHpJ36pIE

    ReplyDelete
  8. Pengenalan kepada regresi linear
    http://www.youtube.com/watch?v=ocGEhiLwDVc

    ReplyDelete
  9. Koefisien
    http://www.youtube.com/watch?v=unil0JmtU0g

    ReplyDelete
  10. Selang keyakinan
    http://www.youtube.com/watch?v=bq9XhIM0gAQ

    ReplyDelete
  11. Teorem Had Memusat
    http://www.youtube.com/watch?v=NBRp6HuN_wk

    ReplyDelete