Presentasi sedang didownload. Silahkan tunggu

Presentasi sedang didownload. Silahkan tunggu

ANALISIS DATA SMT 310 Motivasi  Memahami analisis eksplorasi dan konfirmasi  Landasan statistika deskriptif dan inferensi 

Presentasi serupa


Presentasi berjudul: "ANALISIS DATA SMT 310 Motivasi  Memahami analisis eksplorasi dan konfirmasi  Landasan statistika deskriptif dan inferensi "— Transcript presentasi:

1 ANALISIS DATA SMT 310

2 Motivasi  Memahami analisis eksplorasi dan konfirmasi  Landasan statistika deskriptif dan inferensi  Bersinergi dengan komputasi statistik untuk meng- upgrade kemampuan analisis data

3 Deskripsi  Penyusunan dan rangkuman data numerik  Penyajian data univariat  Transformasi data  Sampel acak  Statistika konfirmasi  Analisis variansi  Hubungan antara dua variabel  Analisis data kategorik

4 Referensi  Erickson, Bonnie H & Nosanchuk Memahami Data : Statistika untuk Ilmu Sosial. (terjemahan RK. Sembiring & Manase Malo). Jakarta: LP3ES  Griffiths D., Stirling W.D, Weldon K.L Understanding Data : Principles and Practice of Statistics. Brisbane : John Willey & Sons

5 Kontrak  Penilaian  Bobot :  Tugas : 20%  Kuis: 15%  Usip: 25%  Uas: 40%

6 REVIEW  STATISTIKA ?  STATISTIK ?  STATISTIKA DESKRIPTIF ?  Statistika inferensi  Populasi  Sampel  Parameter  Statistik

7 Data  Nilai ujian metode stastistik 20 orang mahasiswa adalah :  Misalkan diketahui nilai ujian komputasi statistika 50 mahasiswa ,759,867,157,158,269,560,644,27651,2 48,463,967,856,26068,248,54672,652 42,557,270,25762,270,35076,87465,1 49,164,774,663,66372,275,37555,467,7 43,176,568,759,963,572,67773,556,377,3

8  Banyaknya penjualan HP di suatu toko : Merek HPPenjualan Nokia56 SE45 Samsung32 LG22 Lain45

9 Skala pengukuran  Nominal:  Ordinal:  Interval:  Rasio: Contoh:  Nominal: jenis pekerjaan, warna  Ordinal: kepangkatan, tingkat pendidikan  Interval: tahun kalender (Masehi, Hijriyah), temperatur  (Celcius, Fahrenheit)  Rasio: berat, panjang, isi

10 Statistika deskriptif  Metode atau cara-cara yang digunakan untuk meringkas dan menyajikan data dalam bentuk tabel, grafik atau ringkasan numerik data.

11 Grafik Stem-and-leaf  Untuk menunjukkan bentuk distribusi data  Data berupa angka dengan minimal dua digit  Contoh (Data penghasilan buruh): Stem= 10, Leaf = 1

12 Why study statistics? Make decision without complete informations Understanding population, sample Parameter, statistic Descriptive and inferential statistics Intro…

13 glossary A population is the collection of all items of interest or under investigation N represents the population size A sample is an observed subset of the population n represents the sample size A parameter is a specific characteristic of a population Mean, Variance, Standard Deviation, Proportion, etc. A statistic is a specific characteristic of a sample Mean, Variance, Standard Deviation, Proportion, etc.

14 Population vs. Sample a b c d ef gh i jk l m n o p q rs t u v w x y z PopulationSample b c g i n o r u y Values calculated using population data are called parameters Values computed from sample data are called statistics

15 Examples of Populations Incomes of all families living in yogyakarta All women with pregnancy problem. Grade point averages of all the students in your university …

16 Random sampling Simple random sampling is a procedure in which each member of the population is chosen strictly by chance, each member of the population is equally likely to be chosen, and every possible sample of n objects is equally likely to be chosen The resulting sample is called a random sample

17 Descriptive and Inferential Statistics Two branches of statistics: Descriptive statistics Collecting, summarizing, and processing data to transform data into information Inferential statistics Provide the bases for predictions, forecasts, and estimates that are used to transform information into knowledge and decision

18 Descriptive Statistics Collect data e.g., Survey Present data e.g., Tables and graphs Summarize data e.g., Sample mean =

19 Inferential Statistics Estimation e.g., Estimate the population mean weight using the sample mean weight Hypothesis testing e.g., Test the claim that the population mean weight is 120 pounds Inference is the process of drawing conclusions or making decisions about a population based on sample results

20 The Decision Making Process Begin Here: Identify the Problem Data Information Knowledge Decision Descriptive Statistics, Probability, Computers Experience, Theory, Literature, Inferential Statistics, Computers


Download ppt "ANALISIS DATA SMT 310 Motivasi  Memahami analisis eksplorasi dan konfirmasi  Landasan statistika deskriptif dan inferensi "

Presentasi serupa


Iklan oleh Google