### Investigating bivariate measurement data using iNZight - CensusAtSchool New Zealand

MathsNZ Students - - Bivariate Data Investigate bivariate measurement data, with justification. 1 Data Set Information Examples of Correlation Coefficient (r) Separating Variables Sample Internal This site is maintained by Jake Wills. This workshop focuses on key issues when teaching bivariate data and addresses some possible misconceptions. Teaching points are related. Investigate bivariate measurement data Investigate bivariate measurement data, with What is the nature of the relationship between variable 1 and variable 2 for . 49 Find a model Because the trend is linear I will fit a linear model to the data. . Jake Wills Otahuhu College & Westlake Boys High School CensusAtSchool.

Can the results be extended to a wider population? Groupings 21 A morphological study of skull and mandible features was undertaken to examine variation between the most genetically distinct population, occurring on the west coast of the North Island, and the populations around the South Island.

## AS 91581 Achievement Standard.

Univariate and principal component analyses demonstrate that the North Island population can be differentiated from the southern populations on the basis of several skeletal characters. For this question it does not matter which variable goes on each axis.

If the data comes from an experiment then some variables would be classed as input variables and others as output variables. It would make sense to see how an input variable affects an output variable. The input variable would be the explanatory variable and the output variable would be the response variable.

### () Investigate bivariate measurement data - MathsNZ Teachers

Use descriptions of variables rather than variable names- keeps it contextual. This is a reasonable expectation because two different measures on the same body part of an animal could be in proportion to each other. Key point is linear or non-linear. Use of descriptions of variables rather than variable names.

Refer to the graph. This illustrates some reflection. This is to be expected because dolphins with small rostrums would tend to have small values for rostrums widths at base and midlength and dolphins with large rostrums would tend to have large values for rostrums widths at base and midlength. A contextual description is preferable to one using technical terms. However it is appropriate to use terms such as positive, negative or no association, but they are better used after the contextual description.

Higher level considerations You should reflect on the nature of the relationship with respect to the context. At this stage you could acknowledge if the data does not come from a randomised experiment that they have found only a statistical relationship and that this does not necessarily imply a causal relationship between the variables.

- Presentation on theme: "AS 91581 Achievement Standard."— Presentation transcript:
- Add a teaching resource
- Rate this resource:

Alternatively, if the data comes from a suitable experiment they could make a causation claim in their conclusion. Students may acknowledge that other variables which they must name would impact on the response variable, and suggest how they might impact on the variable.

For example, gender, age, etc. How do we work out how much we should charge? Is there a relationship between the GB of a memory stick, and how much is costs? Use the relationship between two variables to make a prediction Analysis Draw a scatter plot of the data.

Use the relationship between two variables to make a prediction Conclusion relationship Describe the relationship between GB and price for the USB sticks. Is it a linear relationship? Use the relationship between two variables to make a prediction Conclusion prediction Use the relationship to make a prediction for 10GB.

Try to imagine painting across the values, draw the ellipse, add the line Use the line to see how much a 10GB memory stick might cost Answer the problem!!

Use the relationship between two variables to make a prediction Reflection Think about where the data came from, what else might effect the price of a USB memory stick, what you could do to extend the investigation.

Write a plan for a bivariate investigation 31 List the steps for a method LO: Write a plan for a bivariate investigation List the steps for a method Identify variables for the investigation Describe how the variables will be measured Explain how the data will be collected Decide how much data to collect 32 LO: Write a plan for a bivariate investigation 33 LO: Write a plan for a bivariate investigation Problem What is the relationship between the size of the hard-drive memory and the selling price for laptops?

**Summarizing Bivariate Data**

Write a plan for a bivariate investigation What is the relationship between the size of the hard-drive memory and the selling price for laptops? What variables will you investigate?

How will you collect data for the investigation? Are the variables things I can measure myself or can I find measures for the variables from somewhere? I can collect data for this investigation by …… Getting ads for laptops being sold that say how big the hard-drive memory is and what price the laptop is being sold for from advertising pamphlets.

How will you measure these variables? What units should I use?

How accurate do I need to be? What equipment do I need?

## 91581 (3.9) Investigate bivariate measurement data

I will measure the variables by using…. What things might affect the measures you take? Does it matter where I get my data from? Do I need to be careful about getting a range of data?

Should I focus my investigation more?

I wonder if things like…………. How many measures will you collect? How much data do I need?