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Data Handling - Data Collection Methods (Surveys, Observations)

Grade 6IB

Review the key concepts, formulae, and examples before starting your quiz.

🔑Concepts

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Data Collection Basics: Data is the raw information or facts gathered to answer a specific research question. It is categorized into Quantitative data (numerical, like the weight of an object) and Qualitative data (descriptive, like the color of eyes).

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Surveys and Questionnaires: A survey involves asking a group of people a set of questions to gather information about their opinions or behaviors. Visual: Imagine a structured sheet with multiple-choice boxes where a respondent ticks their preferred choice, making the data easy to count later.

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Observation Method: This involves watching and recording events or behaviors as they happen in a natural setting without interfering. Visual: Picture a researcher standing near a playground with a clipboard, recording how many children use the slide versus the swing over a 1010-minute period.

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Tally Charts: A tally chart is a primary tool used during data collection to keep a running total of frequencies. Visual: For every item counted, a vertical stroke ∣| is drawn; the fifth stroke is drawn diagonally across the four previous strokes ∣∣∣∣\cancel{||||} to represent a bundle of 55, making final counting much faster.

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Primary vs. Secondary Data: Primary data is information you collect yourself for the first time (e.g., your own experiment results). Secondary data is information collected by someone else that you use (e.g., data from a website, newspaper, or a library book).

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Population and Sample: The 'Population' refers to the entire group you are interested in, while a 'Sample' is a smaller portion of that group used for the study. Visual: A large circle representing a school (Population) with a smaller circle inside it representing one specific grade (Sample).

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Bias in Data Collection: Bias occurs when the data collection process is unfair or skewed toward a particular result. For example, if you only survey people at a library about their favorite hobby, the results might be biased toward reading.

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Closed vs. Open Questions: Surveys use 'Closed Questions' which have fixed options (e.g., Yes/No) for easy analysis, or 'Open Questions' which allow respondents to answer in their own words for more detailed information.

📐Formulae

Relative Frequency=Frequency of CategoryTotal Number of Observations\text{Relative Frequency} = \frac{\text{Frequency of Category}}{\text{Total Number of Observations}}

Percentage=FrequencyTotal Count×100%\text{Percentage} = \frac{\text{Frequency}}{\text{Total Count}} \times 100\%

Range=Maximum Value−Minimum Value\text{Range} = \text{Maximum Value} - \text{Minimum Value}

💡Examples

Problem 1:

A student observes cars passing a school gate for 1515 minutes. He records the following tallies for car colors: Red (∣∣∣∣\cancel{||||} ∣∣||), Blue (∣∣∣∣\cancel{||||} ∣∣∣∣\cancel{||||}), and Silver (∣∣∣|||). Create a frequency table and calculate the percentage of Blue cars.

Solution:

  1. Identify the frequencies from the tallies:
  • Red: 5+2=75 + 2 = 7
  • Blue: 5+5=105 + 5 = 10
  • Silver: 33
  1. Calculate the total number of cars: 7+10+3=207 + 10 + 3 = 20
  2. Apply the percentage formula for Blue cars: Percentage=1020×100=50%\text{Percentage} = \frac{10}{20} \times 100 = 50\%

Explanation:

We first translate the visual tally marks into numerical frequencies. Then, we find the total sum of all observations to use as the denominator in our percentage calculation.

Problem 2:

Determine if the following data collection scenario is biased and identify if it is Primary or Secondary data: 'To find out the most popular sport in a city, a researcher surveys 5050 people entering a football stadium.'

Solution:

  1. Type of Data: Primary Data. Because the researcher is conducting the survey and gathering the information directly.
  2. Bias Check: Yes, it is biased.
  3. Reasoning: People entering a football stadium are more likely to prefer football over other sports, so the sample is not representative of the whole city.

Explanation:

Primary data is identified by the researcher performing the work. Bias is identified by looking at whether the location or group chosen (the football stadium) unfairly influences the outcome of the question.