Hypothesis vs Prediction Hypothesis is a propounded explanation

Hypothesis vs Prediction

Hypothesis is a propounded explanation for the happening of a particular phenomenon, whose development is based on specific evidence. v v v It should be clear and precise. It should be stated simply. It must be specific. When developing a hypothesis think about any observations or previous knowledge you know about the variables. It should correlate variables. It should be consistent with Express what you think will be the effect of changing one of the variables most known facts. (Independent variable) on the other variable you expect to change (Dependent variable). v It should be capable of being tested. Develop your hypothesis using a statement. v It must explain, what it claims A example of a hypothesis statement would be, As the (independent variable) ( to explain. describe how you would change it) , then the (dependent variable ) will (describe the effect)

Prediction is forecasting of future events, which is sometimes based on evidence or sometimes, on a person’s instinct or gut feeling. Collect data using your senses, remember you use your senses to make observations. Search for patterns of behavior and or characteristics. Develop statements about you think future observations will be. Test the prediction and observe what happens.

Hypothesis or Prediction? Flashlight not working…. 1) The flashlight batteries are dead. (Hypothesis) 2) Replacing the batteries will make the flashlight work. (Prediction)

Hypothesis or Prediction? The plant is dying…. 1) Watering the plant will revive it (Prediction) 2) The plant is not getting enough sunlight (Hypothesis)

Hypothesis or Prediction? A hypothesis is a proposed explanation, a prediction is the expected result of a test that is derived, by deduction, from a hypothesis

Scientific Theory A scientific theory is an in-depth explanation of the observed phenomenon. A set of statements that, when taken together, attempt to explain a broad class of related phenomena. There are 4 Main Characteristics of a Good Theory: 1. Organizes & Explains Existing Data and Thus Provides a Framework for Interpreting New Data 2. Is Parsimonious - The assumptions introduced to explain a thing must not be multiplied beyond necessity. 3. Productive - Generates New Ideas & Research Studies. 4. Falsifiable - Capable of being proven incorrect. Theory Hypothesis Prediction Increasing specificity (The more specific the question/statement gets) Increasing ability to be proven incorrect While a hypothesis attempts to explain a specific puzzling observation (or group of closely-related observations), a theory is more complex, more general, and more abstract and may even reflect the convergence of various hypotheses.

Scientific Law vs Theory Theories explain why we observe what we do and laws describe what happens. https: //youtu. be/P 30 Qlw. Ss. Uic

Qualitative Data Descriptive Data Qualitative data tends to answer questions about the ‘what’, ‘how’ and ‘why’ of a phenomenon, rather than questions of ‘how many’ or ‘how much’. Qualitative analysis allows for a detailed examination of the thoughts, feelings, opinions and/or experiences of individuals, groups or communities. Types of qualitative data How to get qualitative data In a school setting, qualitative data may include: Interview Notes from classroom observations Focus Groups A student’s work sample with comments from their teacher Surveys Feedback from a teacher about a student’s progress Case Studies A transcript from a focus group with parents Observation Audio/visual recordings of a class A transcript from a staff meeting

Qualitative Data Qualitative analysis can also be useful for providing a narrative around quantitative data. Quantitative data (e. g. test scores) may tell you that your student’s NAPLAN scores have improved over time. You may then want to use qualitative data (e. g. classroom observation, a focus group with teachers) to determine how and why scores have improved. Qualitative data can be harder to analyze than quantitative data, as the data collected is not inherently objective, and thus can be open to multiple interpretations.

Quantitative Data Numerical Data Quantitative data is any information that can be reduced to a set of numbers. Any information from which you can create averages, differences, or totals is quantitative data. Types of quantitative data Student assessment scores and other student outcomes Aggregates of responses from surveys Financial or Human Resources (HR) information

Quantitative Data Numerical Data Quantitative analysis is focused on combining information across a group or multiple groups of people, and using this to draw out wider trends. Quantitative data can also allow you to be more precise with particular statements. Because quantitative analysis is focused on drawing out trends across a number of people, it is less effective at providing a lot of detail about an individual, or explaining why these trends have come about. Often, analysis using quantitative data answers broad questions, but may lead you to ask more specific questions. Answering these more specific questions may require follow-up qualitative investigation.

Induction and Deduction in Science Induction: Observing thought & behavior and looking for generalities. Deduction: Testing the implications of a theory.

Scientific Method Video https: //www. youtube. com/watch? v=SMGRe 824 kak&fe ature=youtu. be