Is defined as the art and science of collecting analyzing presenting and interpreting data?

Presentation on theme: "Unit 1: Statistics and Statistical Thinking Statistics is the science of data Statistics involves collecting, classifying, summarizing, organizing, analyzing."— Presentation transcript:

1 Unit 1: Statistics and Statistical Thinking Statistics is the science of data Statistics involves collecting, classifying, summarizing, organizing, analyzing and interpreting numerical information Statistics is used in several different disciplines (scientific and non-scientific) to make decision and draw conclusions based on data.

2 For instance: In the pharmaceutical industry. It is impossible to test every drug for every person that may require it. So the industry needs a statistician. In business, managers must often decide whom to offer their company’s products to such as a credit card company must asses how risky a potential customer is. An individual who needs to lose weight for his upcoming new film. He needs to see data of successful diet.

3 Weight Diet12345678 Diet 1310 304300290285280284 Diet 2310312308304300295290289 Diet 3310307306303301299297295 Diet 4310308305303297294290287 Average weight loss on Various diets across 8 weeks Based on these numbers, which diet should he/she addopt?

4 two types of statistics Descriptive statistics: utilize numerical and graphical method to look for patterns in a data set, to summarize information revealed in a data set, and to present the information in a convenient form that individuals can use to make decisions. The main goal of descriptive statistics is to describe a data set. The class of descriptive statistics include both numerical measures (e.g. Mean, Median) or graphical displays of data (e.g. Charts or graphs) Inferential statistics: utilize sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data.

5 descriptive statistics Look at example of the table of various diets What informations provided by the table?  The most significance of diet process is Diet 1  Furthermore, Diet 1 is not stable (see week 7 & 8)  Diet 4 shows a steady decline in weight loss  One can make an educated decision suitable for his/her personal weight loss goals.

6 inferential statistics The main goal is to make a conslusion about a population based on a sample of a population. Inferential statistics mostly uses hypethesis testing. Key Definition: Experimental unit (an object upon which data is colletced) Population (a set of units that is of interest to study) Variable (a characteristic or property of an individual experimental unit) Sample (a subset of the units of a population)

7 statistical hypothesis An educated guess about the relationship between two (or more) variables. Two main variables:  Independent variable (the variable that represents the inputs to the dependent variable, or the variable that can be manipulated to see if they are the cause.  Dependent variable (the variable which represents the effect that is being tested

8 a case of statitical hypothesis A literature teacher has a hypothesis that by demanding the students to read a novel in a week for 16 meetings, the students are able to be self- motivated in reading habit rather than those who are accustomed to lecturing in every meeting. Ind. Variable : reading a novel per week Dep. Variable: self-motivation Since it is impossible to take all students as the sample, so the teacher is to take a sample to generalize the entire population.

9 key steps of problem Descriptive Define the population (or sample) of interest Select the variables that are going to be investigated Select the tables, graphs, or numerical summary tool Identify patterns in the data Inferential Define the population of interest Select the variables that are going to be investigated Select a sample of population units Run the statistical tests on sample Generalize the result to your population and draw conclusions

10 types of data Qualitative Data Measurement that cannot be measured on a natural numerical scale Measurement can only be classified into one or more groups of categories Example: brands of shoes (Nike, Adidas, or K-Swiss), gender (male or female) Quantitative Data Measurement that can be recorded on a natrually occuring scale Example: people’s salary in a year

11 take-home assignment Discuss the difference between descriptive and inferential statistics 1.Give an example of research question that would use an inferential statistic solution 2.Identify the independent and dependent variable in the following research question: A production manager is interested in knowing if employees are effective if they work a shorter work week. To answer his question he proposes the following research question: Do more widgets get made if employees work 4 days a week or 5 days a week? 3.What is the difference between population and sample? 4.Write about a decision you made once in your life time using descriptive statistics!

What is the art and science of collecting presenting analyzing and interpreting data?

Statistics is the art and science of collecting, organising, analysing, interpreting and presenting quantitative and qualitative data for the purpose of drawing scientifically founded conclusions among interdisciplinary applications.

What is the science of collecting and analyzing data?

Statistics is the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole population from those in a representative sample.

Is the science and art of collecting analyzing and drawing conclusions from data?

Statistics is the science and art of collecting, analyzing, and drawing conclusions from data.  Ask Questions: Clarify the research problem and ask one or more valid statistics questions.  Collect Data: Design and carry out an appropriate plan to collect the data.

Which term refers to the science of collecting organizing and interpreting of data?

Statistics is the science of collecting, organizing, analyzing, and interpreting data in order to make decisions.