Data Handling Data Collection and data analysis.pptx

data Collection, Data presentation and data analysis

1. Data Handling

2. What is data Collection? Example: Collecting data on “How many boarder students of GomdarCS are not happy”

3. Sample -Selecting the group that you will actually collect data from in your research Should be at least 10% of population

4. How to collect reliable and unbiased data through random sampling. Simple Random Sampling You want unbiased sample from your school. You can write everyone's name on a slip of paper, toss them all into a hat, and then pull out a few slips without looking. That’s simple random sampling!

5. 2. Stratified sampling Stratified sampling is a method where you divide a population into smaller groups called strata based on shared characteristics (like age, class, or income), and then randomly pick people from each group Example : If you want to survey 100 students, you don’t just pick randomly. Instead, you: • Take 40 from Class VIII • Take 30 from Class IX • Take 30 from Class X

6. 3. Systematic Sampling Systematic sampling - It’s like choosing every 10th student from a class list to form a sample. Example : If you have 100 students and want to pick 10: • Start at a random number (say, 7) • Then pick every 10th student: 7, 17, 27, 37… until you have 10

7. 4. Cluster Sample Cluster sampling means you divide a population into smaller groups (called clusters), then randomly pick a few of those groups—and study everyone inside them. Imagine you want to find out what students in Samdrup Jongkhar think about math class. Instead of picking students from every school, you: • Divide into school clusters • Randomly choose 2 or 3 schools • Then survey all students in those schools

8. Non random Sampling (Biased Sample) Examples 1 : A teacher wants to know how students feel about school lunch programs. Instead of asking a random mix of students, they only ask class monitors from each grade. Bias : Class monitors may be more disciplined or positive, and their views might not reflect the general student body. Examples 2: A researcher wants to study students’ attitudes toward environmental protection in Bhutan. They only collect data from schools in Thimphu and Phuentsholing. Bias : Students in rural areas like Pemagatshel or Zhemgang may have different experiences and values, especially with nature and conservation.

9. Data Collection Group Project Group 1 Favorite Local Fruits in the Community Students survey peers or families about their favorite fruits (e.g., mango, guava, banana). Create pie charts and frequency tables. Group 2 Rainfall Measurement Over a Week • Use simple containers to measure daily rainfall. • Introduces units, averages, and data recording. Group 3 Hours Spent on Homework vs. Leisure • Compare time spent on studies, games, TV, mobile. • Ideal for line graphs or double bar charts.

10. Groups 8C

11. Groups 8A

12. Groups 8B

13. Instructions for Project Work Use random sampling techniques to collect data from the class or a designated population based on your questions. Analyze and interpret the data they collected, using appropriate data representation tools.

14. Example A teacher wants to find the study habits of eighth-grade students. Instead of surveying the entire class, the teacher decides to use random sampling to gather information from a representative sample of students. The collected data will be organized in a table to analyze study habits. Step 1: Sampling Sampling Method:  Simple Random Sampling The teacher assigns a unique number to each student in the eighth-grade class. A random number generator is used to select 20% of the class for the survey.

15. Sampled Students: Let's say the random selection includes 10 students out of a class of 50. Randomly selected assigning Student IDs 5, 12, 18, 23, 27, 32, 36, 41, 45, 49 Step 2: Organizing Data ( Survey Questions) The teacher designs a survey with questions about study habits, including hours spent studying per day, 

16. Collected Data: The sampled students respond to the survey, providing information on their study habits. Student ID Hours of Study per Day        36 1 41 4 18 4 23 5 49 3 32 3 5 1 12 2 45 2 27 2

17. Step 3: Analysis Organized Data Table: The collected data is organized in a table for analysis. Student ID Hours of Study per Day 5 1 12 2 18 4 23 5 27 2 32 3 36 1 41 4 45 2 49 3 Analysis:       Average hours of study perday = = = 2.7 Hours per That means in average, students are studying for 2.7 hours per day  

18. Activity 3 : Present data collection and organizing in a Table Example:  Randomly selected 20 students from total students of 75 of class VIII to find out their favorite student’s game activities Favorite Activity Tally Number of Students Football   12 Volleyball   8 Basketball   6 Archery   8 Khuru   6 Others   8

19. Circle graph(Pie Chart) Circle Graph (Pie Chart): Circle graphs are typically used to represent data that can be divided into categories or parts of a whole. They are effective for showing the composition or relative proportions of different categories within a dataset For example : To show number of favorite fruits in your class.

20. Draw Pie Chart Circle graph uses central angles or percentages to represent the data values Example: Time spent in a day Activities number of hours Browsing Internet 4 household chores 3 meal time 2 sleeping 7 others 8 Step 1 : C onvert each value( number of hours into central angle) Browsing internet = 360 = Household chores = = Meal time = Sleeping = Others = Use Protector to draw the Pie chart  

21. Angle to percent(%) The above angles can also be changed to percent using Browsing internet = 100 = 16.6 % Household chores = = 12.5  

22. Sometimes data could be in percentage. To convert it into a central angle, use the decimal equivalent of percentage ( example 40 % means 0.4) and multiply by 360. Example : 33 % =  

23. You DO

24. Histogram A histogram is a graphical representation of data that involves organizing data into intervals called bins and displaying the frequency or relative frequency of data points within each bin using rectangular bars. Histograms are used to visually represent the distribution of data and are particularly useful for identifying patterns, trends, and outliers in the data

25. Collect Your Data:  Gather the continuous numerical data you want to analyze.  Determine the Bins:  Decide on the number of bins (or intervals) and their sizes. The bins should be of equal width and cover the entire range of your data.  Create a Frequency Table:  Count how many data points fall into each bin and record the count (frequency) for each bin.  Draw the Axes:  Draw a horizontal (x) axis and a vertical (y) axis.  Label the Axes:  Label the horizontal axis with the bins or intervals, and label the vertical axis with the frequencies.  Title the Graph:  Give your histogram a clear, descriptive title that explains what the data represents.  Draw the Bars:  For each bin, draw a bar whose height is equal to its frequency. The bars should be drawn adjacent to each other without any gaps to indicate the continuous nature of the data.    How to create histogram.

26. We do 36 25 38 46 55 68 72 55 36 38 67 45 22 48 91 46 52 61 58 55 Bin Frequency Scores Included in Bin 20-30 2 25,22 30-40 4 36,38,36,38 40-50 4 46,45,48,46 50-60 5 55,55,52,58,55 60-70 3 68,67,61 70-80 1 72 80-90 - 90-100 1 91

27. You Do Create Histogram on following data set Exam Scores (out of 100): 85, 78, 90, 92, 65, 75, 80, 88, 72, 68, 95, 79, 83, 87, 70, 62, 91, 84, 76, 93 What is the range of exam scores? How many students scored between 80 and 90? Is the distribution of scores symmetric or skewed? Why?

28. b) Heights of Students (in inches): 60, 62, 64, 65, 66, 67, 67, 68, 69, 69, 70, 70, 70, 71, 72, 72, 73, 73, 74, 75 What is the tallest height in the dataset? How many students are between 65 and 70 inches tall? Describe the shape of the histogram.

29. Activity 2 Create a histogram for the following data distribution: Create a histogram for the following data distribution: Class intervals 50-60 60-70 70-80 80-90 90-100 100-110 Frequency 30 25 45 15 20 40 17 20 24 26 27 30 38 34 40 35 47 55 58 41 44 49 45 48 44 54 50 60 58 63 20 The time taken (in seconds) by 25 students to solve a problem was :