The Fundamentals of Statistics

1. The Fundamentalsof Statistics Hartanto, SIP, MA Ilmu Hubungan Internasional Fakultas Ilmu Sosial dan Ekonomi Universitas Respati Yogyakarta 2015

2. You’ve already learned that statistics is about analyzing things. Althoughnumbers was the word used to represent things in the opening of this chapter,the first three words ofstatistics, population, sample, and variable, help you tobetter identify what you analyze with statistics. The First Three Words of Statistics

3. Population • Concept • All the members of a group about which you want to draw a conclusion. • Examples • All U.S. citizens who are currently registered to vote. • All patients treated at a particular hospital last year • All students who are currently registered in Respati University

4. Sample • Concept • The part of the population selected for analysis. • Examples • The registered voters selected to participate in a recent surveyconcerning their intention to vote in the next election. • The patients selected to fill out a patient satisfaction questionnaire • 10 registered students selected to participate in Student National Congress.

5. Example Populasi

6. Variable • Concept • A characteristic of an item or an individual that will be analyzed using statistics. • Konsep yang mengandung variasi nilai didalamnya. Nilai tersebut paling sedikit mengandung dua klasifikasi. • Examples • Gender (Male, Female). • The party affiliation of a registered voter (Demokrat, PDIP, Golkar). • The publishing category (hardcover, trade paperback, mass-market paperback, textbook) of a book. • The number of televisions in a household. • Interpretation • All the variables taken together form the data of ananalysis. Although people often say that they are analyzing their data, theyare, more precisely, analyzing their variables.

7. Types of Variable

8. Important Points • All variables should have an operational definition—that is, a universallyaccepted meaning that is understood by all associated with an analysis.Without operational definitions, confusion can occur. • A famous example ofsuch confusion • The tallying of votes in Florida during the 2000 U.S. Presidentialelection in which, at various times, nine different definitions of avalid ballot were used. (A later analysis1 determined that three of these definitions,including one pursued by Al Gore, led to margins of victory forGeorge Bush that ranged from 225 to 493 votes and that the six others,including one pursued by George Bush, led to margins of victory for Al Gorethat ranged from 42 to 171 votes.)

9. Afteryou have identified the variables from the population or sample understudy, you can define the parameters and statistics that your analysis willdetermine. The Fourth and fifth Words

10. Parameter • Concept • A numerical measure that describesa variable (characteristic) of a population. • Examples • The percentage of all registered voters who intend to vote in the next election. • The percentage of all patients who are very satisfied with the care they received.

11. Example • 20% Mahasiswa UNRIYO adalah Laki-Laki. • 30% Mahasiswa yang mengambil mata kuliah Pengantar Statistik Sosial adalah Perempuan • Angka 20% dan 30% itulah yang disebut parameter.

12. Statistic • Concept • A numerical measure that describes a variable (characteristic)of a sample (part of a population). • Statistik sebagai ilmu yang bertujuan untuk mengumpulkan data, mengklasifikasikan data, menyusun data, menyajikan data, menginterpretasikan data serta menyimpulkan berdasarkan data

13. Statistic • Examples • The percentage of registered voters in a sample who intend tovote in the next election. • The percentage of patients in a sample who are verysatisfied with the care they received. • Interpretation • Calculating statistics for a sample is the most commonactivity because collecting population data is impractical in most actual decision-making situations.

14. Fundamental Characteristic of Statistics • Statistik bekerja dengan angka-angka. Angka angka ini dalam statistik mempunyai dua arti yaitu angka sebagai jumlah yang menunjukkan frekuensi, dan angka yang menunjukkan nilai atau harga misalnya nilai rapor, angka kecerdasan. • Statistik bersifat obyektif. Kerja statistik menutup pintu bagi masuknya unsur- unsur subyektif yang dapat menyulap keinginan menjadi kebenaran. Statistik sebagai alat penilai kenyataan tak dapat bicara lain kecuali apa adanya. Adapun makna apa dan bagaimana menggunakan kenyataan statistik itu adalah persoalan di luar statistik. • Statistik bersifat universal dalam arti dapat digunakan hampir dalam semua bidang penyelidikan.

15. Example Apakah Anda setuju Indonesia memiliki PLTN? 40% Tidak Setuju 30% Setuju 30% Tidak Tahu Survey dilakukan dengan Sample 250 orang dari Populasi 500 orang yang Berpendidikan Sarjana.

16. You can use parameters and statistics either to describe your variables or toreach conclusions about your data. These two uses define the two branchesof statistics: descriptive statistics and inferential statistics. The Branches of Statistics

17. Descriptive Statistics • Concept • The branch of statistics that focuses on collecting, summarizing,and presenting a set of data. • statistik yang bersifat menggambarkan gejala atau fenomena agar mudah dipahami masyarakat umum. • Examples • The mean age of citizens who live in a certain geographical area. • The mean length of all books about statistics.

18. Descriptive Statistics • Interpretation • You are most likely to be familiar with this branch ofstatistics because many examples arise in everyday life. Descriptive statisticsserves as the basis for analysis and discussion in fields as diverse as securitiestrading, the social sciences, government, the health sciences, and professionalsports. Descriptive methods can seem deceptively easy to apply because theyare often easily accessible in calculating and computing devices.

19. Inferential Statistics • Concept • The branch of statistics that analyzes sample data to reach conclusions about a population. • Statistik yang digunakan untuk kepentingan penyimpulan dalam kerangka sebuah penelitian dengan berdasarkan data yang ada. • Example • A survey that sampled 1,264 women found that 45% of thosepolled considered friends or family as their most trusted shopping advisersand only 7% consideredadvertising as their most trusted shopping adviser.

20. Inferential Statistics • Interpretation • When you use inferential statistics, you start with ahypothesis and look to see whether the data are consistent with that hypothesis. • This deeper level of analysis means that inferential statistical methodscan be easily misapplied or misconstrued, and that many inferential methodsrequire a calculating or computing device.

21. You begin every statistical analysis by identifying the source of the data. Among the important sources of data are published sources,experiments,and surveys. SOURCES OF DATA

22. Published Sources • Concept • Data available in print or in electronic form, including datafound on Internet websites. Primary data sources are those published by theindividual or group that collected the data. Secondary data sources are those compiled from primary sources • Example • Many U.S. federal agencies, including the Census Bureau, publishprimary data sources that are available at the www.fedstats.gov website. • Business news sections of daily newspapers commonly publish secondarysource data compiled by business organizations and government agencies.

23. Published Sources • Interpretation • You should always consider the possible bias of thepublisher and whether the data contain all the necessary and relevant variableswhen using published sources. Remember, too, that anyone can publish data on the Internet.

24. Experiments • Concept • A study that examines the effect on a variable of varying thevalue(s) of another variable or variables, while keeping all other things equal.A typical experiment contains both a treatment group and a control group.The treatment group consists of those individuals or things that receive thetreatment(s) being studied. The controlgroup consists of those individuals orthingsthat do not receive the treatment(s) being studied. • Example • Pharmaceutical companies use experiments to determinewhether a new drug is effective. A group of patients who have many similarcharacteristics is divided into two subgroups. Members of one group, thetreatment group, receive the new drug. Members of the other group, the controlgroup, often receive a placebo, a substance that has no medical effect.After a time period, statistics about each group are compared.

25. Experiments • Interpretation • Proper experiments are either single-blind or double-blind.A study is a single-blind experiment if only the researcher conductingthe study knows the identities of the members of the treatment and controlgroups. If neither the researcher nor study participants know who is in thetreatment group and who is in the control group, the study is a double-blind experiment. • When conducting experiments that involve placebos, researchers also have to consider the placebo effect—that is, whether people in the control group willimprove because they believe they are getting a real substance that isintended to produce a positive result. When a control group shows as muchimprovement as the treatment group, a researcher can conclude that theplacebo effect is a significant factor in the improvements of both groups.

26. Surveys • Concept • A process that uses questionnaires orsimilar means to gathervalues for theresponses from a set of participants. • Examples • The decennial U.S. census mail-in form. • A poll of likely voters. • A website instant poll or “question of the day • Interpretation • Surveys are either informal, open to anyone whowants to participate; targeted, directed toward a specific group of individuals;or include people chosen at random. The type of survey affects how the datacollected can be used and interpreted.

27. I’m open for your questions Thank You !