Probability is especially important in statistics because of the many principles and procedures based upon this concept. Indeed, probability plays a special role in all our lives, because we use it to measure uncertainty. We are continually faced with decisions leading to uncertain outcomes, and we rely on probability to help us make our choice. Think of the planned outdoor activities, such as picnics or boating, you canceled because the chance of bad weather seemed too likely. Remember those nights before examinations when you decided not to study some topics, because they probably would not be covered on the test?

A probability is a numerical value that measures the uncertainty that a particular event will occur. The probability of an event ordinarily represents the proportion of times under identical circumstances that the outcome can be expected to occur. We refer to this value as the event’s long-run frequency of occurrence. The probability that the head side will slow when a fair coin is tossed is 1/2. This can be verified experimentally by tossing a coin several times and observing that “heads” occur about one-half of those times. Read the rest of this entry »

Gorge Udny Yule said:

“Measurement does not necessarily mean progress. Failing the possibility of measuring that which you desire, the lust for measurement may, for example, merely result in your measuring something else-and perhaps forgetting the difference- or in ignoring some things because they cannot be measured…”

We have said that descriptive statistics involves the arrangment and display of observed data, which are then summarize and analyzed by means of inferential statistics in order to reach some decision. The manner in which the data are described and the procedures followed for their analysis depend upon the decision-making goal and the nature of the data.

The weight of a sample of 40 statistic students in STIE DEWANTARA BOGOR is shown in table 1 below. If we wish to describe this sample, how should we proceed?

Table 1

_______________________________

Weight of 40 Statistic Students

in STIE DEWANTARA BOGOR

________________________________

78 72 74 79 74 71 75 74 72 68

72 73 72 74 75 74 73 74 65 72

66 75 80 69 82 73 74 72 79 71

70 75 71 70 70 70 75 76 77 67

_________________________________

These are the steps how to proceed that data to become Frequency Distribution.

1. Arrange the data

Table 2

_______________________________

Weight of 40 Statistic Students

in STIE DEWANTARA BOGOR

________________________________

65 66 67 68 69 70 70 70 70 71

71 71 72 72 72 72 72 72 73 73

73 74 74 74 74 74 74 74 75 75

75 75 75 76 77 78 79 79 80 82

_________________________________

2. Range (R) = 82 – 65 = 17

3.  Sum of the class (k) =

k = 1 + 3,3 log n (Sturgess Way)

k = 1 + 3,3 log 40

= 1 + 5,3 = 6,3 = 6

4. Class interval (i) :

i = 17/6 = 2,83 = 3

Here is the results shown on the table 3 below:

Table 3

Frequency Distributions

Weight of 40 Statistic Students

in STIE DEWANTARA BOGOR

____________________________________

Weight (Kg)                       Frequency

———————————————————–

65 – 67                                      3

68 – 70                                      6

71 – 73                                      12

74 – 76                                      13

77 – 79                                      4

80 – 82                                      2

——————————————————

TOTAL                                     40

__________________________________

Hopefully this article can be useful to helps you studying Statistics…

See you next time…

The emphasis upon the decision-makin aspects of statistics is a recent one. In its early years, the study of statistics largerly consisted of methodology for summarizing or describing numerical data. Any aspects facilitating choice were secondary in importance to the then essentially reportorial nature of the subject. Tis area of study has become known as descriptive statistics because it is concerned largerly with summary calculations and graphical displays. These methods are in contrast with the modern approach, where generalizations are made about the whole, called the population, by investigating a portion, reffered to as the sample.

Read the rest of this entry »

A. Pendahuluan

Salah satu langkah dalam penelitian ilmiah adalah menentukan populasi dan sample. Kesalahan dalam menentukan sampel dapat berakibat fatal, karena sampel menjadi tidak representatif, dan hasil penelitian tidak akan dapat mencerminkan keadaan yang sebenarnya. Oleh karena itu memilih tenik penentuan sampel yang tepat menjadi sangat penting untuk mendapatkan sampel yang representatif.

B. Pengertian Populasi Dan Sampel

Dalam suatu penelitian adakalanya peneliti meneliti semua sumber data yang direncanakan, agar data dan informasi yang diperoleh banyak dan bervariasi sehingga diharapkan hasilnya tidak jauh berbeda dari kenyataan. Akan tetapi dalam kenyataannya tidak semua populasi dapat diteliti karena suatu sebab yang tidak memungkinkan. Penelitian ilmiah boleh dikata hampir selalu hanya dilakukan terhadap sebagian saja dari hal-hal yang sebenarnya hendak diteliti.

Populasi adalah wilayah generalisasi yang terdiri atas obyek/subyek yang mempunyai kuantitas dan karakteristik tertentu yang ditetapkan oleh peneliti untuk dipelajari dan kemudian ditarik kesimpulannya. Jadi populasi bukan hanya orang, tetapi juga benda-benda alam lain. Populasi juga bukan sekedar jumlah yang ada pada obyek/subyek yang dipelajari, tetapi meliputi seluruh karakteristik/sifat yang dimiliki oleh subyek atau obyek itu.

Misalnya akan dilakukan penelitian di lembaga X, maka lembaga X ini merupakan populasi. Lembaga X mempunyai sejumlah orang/subyek dan obyek yang lain. Hal ini berarti populasi dalam arti jumlah/kuantitas. Tetapi lermbaga X juga mempunyai karakteristik orang-orangnya, misalnya motivasi kerjanya, disiplin kerjanya, kepemimpinannya, iklim organisasinya dan lain-lain. Juga mempunyai karakteristik obyek yang lain, misalnya kebijakan, prosedur kerja, tata ruang produk yang dihasilkan dan lain-lain. Yang terakhir berarti populasi dalam arti karakteristik. Satu orangpun dapat digunakan sebagai populasi, karena satu orang mempunyai berbagai karakteristik, misalnya gaya bicaranya, disiplin pribadi, hobi, cara bergaul, kepemimpinannya dan lain-lain. Misalnya akan melakukan penelitian tentang kepemimpinan presiden Y, maka kepemimpinan itu merupakan sample dari semua karakteristik yang dimiliki presiden Y. Jadi sample adalah bagian dari jumlah dan karakteristik yang dimiliki oleh populasi ( Sugiyono, 2002:57 ).

C. Penggunaan Populasi dan Sampel

Read the rest of this entry »

Nowadays I have already upload my statistic Handout about “Fraktil (Kuartil, Desil, Persentil)” on my website. You can easily download by click here
I really hope that my handout will guide you well on your learning about statistic, especially in this part.
If there is any mistakes, you can send me an e-mail to: info@boeditea.web.id or you can write down on my facebook. Thanks for your visiting to this simply site

Module Basic Statistic (Statistik 1) You can easily download.. just click here