+ introduction to data analysis *training session*

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+ Introduction to Data Analysis *Training Session*

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Page 1: + Introduction to Data Analysis *Training Session*

+

Introduction to Data Analysis*Training Session*

Page 2: + Introduction to Data Analysis *Training Session*

+What is Data?

Data is a collection of facts.

Data can be in the form of numbers, words, measurements, observations or even just descriptions of things.

In most cases, data needs to be interpreted and analyzed to provide useful information.

For example:

The height of a mountain is considered a data point. Gathering more data on the landscape and temperatures on the mountain gives us very good information about what the mountain area might look like. One could then use the data and information to create a guide on the best way to climb the mountain.

Page 3: + Introduction to Data Analysis *Training Session*

+Why is Data important?

Gathering information and data is an important way to help people make decisions about topics of interest.

Gathering data can help identify needs and problems in a community. It can be used to find solutions to the issues.

Information and data gathering can help you in getting to know the people around you.

Page 4: + Introduction to Data Analysis *Training Session*

+Qualitative versus Quantitative

Data can be qualitative, where it describes something.

Data can be quantitative, it will be in number form.

Discrete data is counted and continuous data is measured.

Page 5: + Introduction to Data Analysis *Training Session*

+An example

What do we know about the elephant?

Qualitative: It is gray It is large It does not have fur

Quantitative: It has four legs (discrete) It has one trunk (discrete) It weighs 7,543.2 kg (continuous) It can be up to 13.5 feet tall (continuous)

Page 6: + Introduction to Data Analysis *Training Session*

+Collecting Data

Data can be collected in many different ways. The simplest way is by observing:

An Example:

You want to find out how many children use the Hello World terminal every day

You would simply sit next to the Hello World terminal for the day and count how many children use the terminal.

Page 7: + Introduction to Data Analysis *Training Session*

+Survey

Surveys can help answer any other question that might be of interest.

Surveys can also helps us to decide if things are going well or not going so well.

There are four steps to a successful survey: Create the questions Ask the questions Count and analyze the results Present the results

Page 8: + Introduction to Data Analysis *Training Session*

+a. Creating Survey Questions

Questions can be very simple: Example: What is your favorite color? What is your favorite activity in your free time?

You can give people a set of answers to choose from (a closed-ended question) or you can leave the question open ended (an open-ended question) and let them fill in the answer.

An Example: Close-Ended Question

What is your favorite color? Choose one of the following: Red Green Blue

Open-Ended Question What is your favorite activity in your free time? Please fill in the

blank: ………….

Page 9: + Introduction to Data Analysis *Training Session*

+b. A Quick Note on Close-Ended Questions Additionally, closed-ended questions can be represented in different ways:

Scaled Answers: This type of answer includes a scale that has opposite words on either side. For example: My feelings about chocolate are:

Strongly Dislike

Dislike Neutral Like Strongly Like

Ranking Answers: This type of answer includes ranking each answer choice. For example: Please rank the following activities from 1 to 5, where 1 is the activity

you like most and 5 is the activity you like least: Playing Football: … Reading: … Playing Games:… Drawing: … Sleeping: …

Page 10: + Introduction to Data Analysis *Training Session*

+c. Asking the Questions

Now that you have created the question, you need to ask people to answer them.

If you have a small population, you can ask everyone. This is called a census

If your population is large, you may not have time to ask everyone. You can choose a sample of the population and only

ask some people the questions you created You can then make a prediction from the sample of how

the population would feel as a whole

Page 11: + Introduction to Data Analysis *Training Session*

+d. Choosing a Sample

When you are selecting your sample, you will want to ask randomly selected people to avoid bias in the answer

For example, bias occurs when you only ask happy looking people your questions. You will never know how all the sad looking people would respond to the questions.

The idea is to pick a sample so that the characteristics of the sample are as close to the general population as possible

Equal number of males and females People of different ages Happy and sad people

An Example:

Let’s say you want to find out what the favorite color of your community is. To help you pick people at random you can use the following tricks:

Sit next to the Hello World terminal and only ask every third person that uses the terminal your questions

Choose people randomly from a list of all users and only ask the people you picked out randomly.

Page 12: + Introduction to Data Analysis *Training Session*

+e. Some More Helpful Tips

You should aim to at least have 20 people answer your questions.

Try to avoid simply asking only people you know already. If someone does not want to answer the questions, it is

ok to record this as: (no answer). It is important to answer questions as truthfully as

possible. Be patient – surveys take time to complete but the pay-

off is very valuable.

Page 13: + Introduction to Data Analysis *Training Session*

+3. Count and Analyze the Results

After you finish asking everyone the questions, you need to look at the results and count them if it is quantitative data.

You can use paper and pen or spreadsheets on the computer to do this.

For example: For finding the favorite colors of the community, you can use a tally and count the number of people who liked each color:

Red ||| 3

Blue ||||| 5

Green || 2

Page 14: + Introduction to Data Analysis *Training Session*

+4. Presenting the Results

Now that you have your results, you will want to show them to other people. Here are a few simple ways of presenting data:

Tables This is a very easy way to show results. Your table should

always have a title, so that people know what you are presenting to them

The Favorite Colors of the Community

Red Blue Green

3 5 2

Page 15: + Introduction to Data Analysis *Training Session*

+4. Presenting the Results (continued) Statistics

You can use statistical methods such as showing the mean number of people per week that use the Hello World terminal.

An Example:

Let’s say that you found the following data on how many people use the Hello World terminal everyday:

Monday: 3 Tuesday: 4 Wednesday: 1 Thursday: 6 Friday: 0 Saturday: 4 Sunday: 3

To find the mean number of people that use the terminal every week, you would add up the number of people each day and divide the sum by the total number of days in the week (7): 3+4+1+6+0+4+3= 21 21/7 = 3

You can then present the result and say that on average, 3 users per week use the Hello World terminal.

Page 16: + Introduction to Data Analysis *Training Session*

+4. Presenting the Results (continued)

The best way to present data is by using graphs.

Bar Graph:

Red

Blue

Green

0 1 2 3 4 5 6

3

5

2

Favorite Color in the Community

Page 17: + Introduction to Data Analysis *Training Session*

+4. Presenting the Results

Column Graph:

Red

Blue

Green

0

1

2

3

4

5

3

5

2

Favorite Color in the Com-munity

Page 18: + Introduction to Data Analysis *Training Session*

+4. Presenting the Results (continued)

Pie Chart:

30%

50%

20%

Favorite Color in the Community

RedBlueGreen

Page 19: + Introduction to Data Analysis *Training Session*

+Thank you for listening!

Please feel free to ask lots of questions