Stage 1 Desired Results

UNIT 1: Collecting Data	Pacing: 3 weeks
*Stage 1 Desired Results*
Established Goals: IC.A.1: Understand statistics as a process for making inferences about population parameters based on a random sample from that population. IC.B.3: Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.	Transfer
	Students will be able to independently use their learning to…. Develop critical thinking skills to evaluate the appropriateness of different data collection methods and recognize potential sources of bias. Enhance their communication skills, being able to clearly articulate the purpose of data collection and the methods used.
	*Meaning*
	Understandings Students will understand… The fundamental purpose of data collection in statistical analysis, recognizing its role in informing decisions and drawing conclusions. The difference between categorical and numerical data, understanding how data types influence the selection of appropriate collection methods. Various sampling methods and recognize the importance of selecting an appropriate technique based on the research question. The principles of survey and questionnaire design, including the impact of question wording, response options, and survey structure on data quality.	Essential Questions Students will keep considering… Why is data collection a crucial step in statistical analysis? What are the different types of data, and how does the type of data influence the data collection process? How do researchers determine the sampling method, and what are the implications of different sampling techniques? How can bias be minimized? How can surveys and questionnaires be designed to gather meaningful and unbiased information?
	*Acquisition*
	Students will know… The different sampling techniques, such as random sampling, stratified sampling, and convenience sampling, and understand when each is appropriate. The various data collection instruments, including surveys, questionnaires, interviews, and observational methods, and understand the strengths and limitations of each. How bias can affect data collection and be aware of strategies to minimize bias, ensuring the collection of accurate and representative data. How technology, such as online surveys, mobile apps, or sensors, can be leveraged in data collection, considering its implications for data accuracy and privacy.	Students will be skilled at… Designing effective surveys and questionnaires, considering factors such as question clarity, response options, and overall survey structure. Implementing various sampling techniques, understanding how to choose an appropriate method based on the research context. Validating data to ensure accuracy and reliability, recognizing and addressing potential errors in the collected data. Using technology tools for data collection, such as statistical software, online survey platforms, or data collection apps.