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Statistika. Konsep dasar dan metoda penggunaannya dalam penelitian. Tujuan :.
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Statistika Konsep dasar dan metoda penggunaannya dalam penelitian

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Tujuan : Untuk memajukan pemikiran yang tertib, runut dan jelas, terutama yang berhubungan dengan pengumpulan dan interpretasi information numerik, serta menyediakan sejumlah teknik statistika yang mempunyai kegunaan yang luas dalam penelitian. Melakukan penyajian, peringkasan dan pencirian information Statistika adalah cara berpikir perihal ketidakpastian .

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Penelitian : Penyelidikan terencana untuk mendapatkan fakta baru, untuk memperkuat atau menolak hasil percobaan terdahulu. Penyelidikan demikian ini akan membantu pengambilan keputusan

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Pertanyaan yang harus dijawab : Untuk setiap perhitungan statistik, selalu muncul pertanyaan mengenai ketelitiannya, berapa angka yang masih dapat dipercaya sebagai akhir dari serangkaian perhitungan yang kita lakukan

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Aplikasi Statistik dibagi menjadi dua bagian : Statistik Deskriptif Menjelaskan/menggambarkan berbagai karakteristik information seperti mean, sexually transmitted disease dev, variansi dan sebagainya Statistik Induktif (Inferensi) Membuat berbagai inferensi terhadap sekumpulan information yang berasal dari suatu sampel. Tindakan inferensi tersebut seperti melakukan perkiraan, peramalan, pengambilan keputusan dan sebagainya.

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Dalam prakteknya kedua bagian statistik tersebut digunakan bersama-sama, umumnya dimulai dengan statistik deskriptif lalu dilanjutkan dengan berbagai analisis statistik untuk inferensi.

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Elemen Statistik. 1. Populasi Sekumpulan information yang mengidentifikasikan suatu fenomena yang tergantung dari kegunaan dan relevansi information yang dikumpulkan. 2. Sampel Sekumpulan information yang diambil/diseleksi dari suatu populasi. ( sampel adalah bagian dari populasi ).

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3. Statistik Inferensi Suatu keputusan, perkiraan atau generalisasi tentang suatu populasi berdasarkan informasi yang terkandung dari suatu sampel 4. Pengukuran Reabilitas dari Statistik Inferensi. Tujuan dari statistik pada dasarnya adalah melakukan deskripsi terhadap information sampel, kemudian melakukan inferensi terhadap populasi information berdasar pada informasi (hasil statistik deskriptif) yang terkandung dalam sampel. Catatan : Karena sampel yang diambil hanya sebagian dari populasi, dapat terjadi predisposition dalam kesimpulannya . Sebagai konsekuensi dari kemungkinan timbulnya berbagai predisposition dalam inferensi, perlu diukur reabilitas dari setiap inferensi yang telah dibuat.

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Tipe Data Statistik. Information Kualitatif a.  Nominal Mis sexual orientation, tgl lahir dsb yang untuk mudahnya dapat dikategorikan dengan angka. (level sama) b. Ordinal Misal selera, dsb (level tidak sama)

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Tipe Data Statistik. Information Kuantitatif a.   Data Interval Data yang memiliki jangkauan Mis pengukuran suhu, Cukup panas antara 50 – 80 derajat C, Panas antara 80 – 110 C, dan Sangat panas antara 110 – 140 C b. Information Rasio. Information dengan tingkat pengukuran ter "tinggi" diantara jenis lainnya. Sehingga dapat dilakukan operasi matematika. Mis jumlah barang, berat badan dsb.

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Statistik Deskriptif Bagian ini lebih berhubungan dengan pengumpulan dan peringkasan information, serta penyajian hasil peringkasan tersebut. Penyajian tabel dan grafik misalnya     1. Distribusi Frekuensi     2. Histogram, Pie graph dsb Dua ukuran penting yang sering digunakan dalam pengambilan keputusan adalah :     1. Mencari Central Tendency (mean, middle, modus)     2. Mencari Ukuran Dispersi (sexually transmitted disease deviasi, variansi) Ukuran lain yang sering digunakan adalah Skewness dan Kurtosis untuk mengetahui kemiringan information.

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Statistical Notation Variabel biasanya ditulis sbg "x" dan "y" Untuk populasi dinotasikan dg huruf besar "N" ("N" for populaces and "n" for tests) Sigma (  ) mewakili operasi penjumlahan

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Statistical Notation X y xy x+1 x 2 2 3 6 3 4 3 5 15 4 9 6 8 48 7 36 4 2 8 5 16

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Statistical Notation S x demonstrates that scores on factor "x" are to be included; S y shows that scores on factor "y" are to be included the past table, S x = 2 + 3 + 6 + 4 = 15 S y = 3 + 5 + 8 + 2 = 18 S x S y = 15*18 = 270

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Statistical Notation S xy demonstrates that the 2 factors (x and y) are to be increased together, then summed. S xy = (2*3) + (3*5) + (6*8) + (4*2) = 77 ( 6 + 15 + 48 + 8 = 77) Note that S xy  (does not equivalent) S x S y (77 versus 270)

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Statistical Notation S (x+1) demonstrates that a steady estimation of 1 is added to every score, then every score is included Remember that operations in enclosure are constantly done first S (x+1) = (2+1) + (3+1) + (6+1) + (4+1) = 19 = ( 3 + 4 + 7 + 5 = 19) Notice that S (x+1)  S x+1 (19 versus 16)

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Statistical Notation  X 2 shows to square each of the x values, then include them up  X 2 = 2² + 3² + 6² + 4² = 65 (= 4 + 9 + 36 + 16=65) Notice that x 2  ( x) 2 (65 versus 225)

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Dalam statistika hal yang withering penting adalah PENGAMATAN

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Perhatikan information berikut : 8, 8, 9, 10 , 11, 12, 12 5, 6, 8, 10 , 12, 14, 15 1, 2, 5, 10 , 15, 18, 19 Dan 8, 9, 10, 10 , 10, 11, 12 5, 7, 9, 10 , 11, 13, 15 1, 5, 8, 10 , 12, 15, 19

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Perhatikan information berikut : 8, 8, 9, 10 , 11, 12, 12 s: 1.6 5, 6, 8, 10 , 12, 14, 15 s: 3.58 1, 2, 5, 10 , 15, 18, 19 s: 6.96 Dan 8, 9, 10, 10 , 10, 11, 12 s: 1.19 5, 7, 9, 10 , 11, 13, 15 s: 3.16 1, 5, 8, 10 , 12, 15, 19 s: 5.60

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Central Tendency CENTRAL TENDENCY: A factual measure that distinguishes a solitary score that is most run of the mill or illustrative of the whole gathering; a solitary score or estimation used to depict a whole dispersion Usually, an esteem that mirrors the center of the conveyance is utilized, in light of the fact that this is the place the majority of the scores heap up No single measure of focal inclination works best in all conditions, so there are 3 unique measures - mean , middle , and mode . Every works best in a particular circumstance

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Central Tendency (Mode) MODE: The score or classification that has the best recurrence; the most widely recognized score To discover the mode, just find the score that seems regularly In a recurrence circulation table, it will be the score with the biggest recurrence esteem In a recurrence chart, it will be the tallest bar or point

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Central Tendency (Mode) Example: A specimen of class ages is given. . . Ages f * The age with the most elevated 23 1 recurrence is 19, with a 22 0 recurrence of 3; thusly, the 21 1 mode is 19. 20 0 19 3 18 2

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Central Tendency (Mode) A circulation may have more than one mode, or pinnacle: A dissemination with 2 modes is said to be bimodal; A dispersion with more than 2 modes is said to be multimodal Example: A specimen of class ages. . . Age f * age 22 and age 19 both 23 1 have a recurrence of 3; if 22 3 this circulation were 21 1 charted, there would be 20 1 2 tops; in this manner this 19 3 appropriation is bimodal - 18 2 both 22 and 19 are modes

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Central Tendency (Mode) Advantages: Easiest to decide The main measure of focal inclination that can be utilized with ostensible (unmitigated) information Disadvantages Sometimes is not an interesting point in the conveyance (bimodal or multimodal) Not delicate to the area of scores in a dissemination Not regularly utilized past the elucidating level

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Central Tendency (Median) MEDIAN: The score that partitions the dispersion precisely fifty-fifty; half of the people in a dissemination have scores at or beneath the middle

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Central Tendency (Median) Method 1 : (Use when N (or n) is an odd number) List the scores from most minimal to most astounding; the center score on the rundown is the middle Example: The ages of a specimen of class individuals are 24, 18, 19, 22, and 20. What is the middle esteem? List the scores from most minimal to most astounding: 18, 19, 20, 22, 24 The center score is 20 - subsequently, that is the middle

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Central Tendency (Median) Method 2: (Use when N (or n) is a much number) List scores all together from least to most noteworthy and find the point somewhere between the center two scores Example: The ages of a specimen of class individuals are 18, 19, 20, 22, 24 and 30. What is the middle age? The scores are as of now recorded from most reduced to most noteworthy; select the center two scores (20, 22) and locate the center point:

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Central Tendency (Mean) MEAN (µ, x ) : The numerical normal of the scores The sum that every individual would get if the aggregate ( x) were partitioned up similarly between everybody in the dissemination Computed by including the greater part of the scores in the conveyance and separating that entirety by the aggregate number of scores Population mean: Sa mple mean:

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Central Tendency (Mean) Note that, while the calculations would yield a similar reply, the images contrast for a populace (  , N) and a specimen ( x, n) Example:

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Central Tendency (Mean) If a consistent is included or subtracted from every score used to figure the mean, the mean will change by the estimation of that steady Example: The class scores on a 15-point test are 8, 4, 12, 14, 4, and 6. The mean of these scores is. . .

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Central Tendency (Mean) Suppose the teacher made a blunder on the test and chose to add 1 indicate everybody\'s score. How might that change the mean? X +1 * The new scores are 9, 5, 13, 15, 5, &7 8+1= 9 * The new

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