How to use...
This doesn't look to dissimilar to PowerPoint. Being new to google presentation it took me a few mins to get use to it - but this video helped me greatly...
There were more youtube clips that I found useful - but for your presentation we don't need to get too technical.
It is more important to have good PPDAC details than to make it look fancy.
OK Review Of Where You're At
In your pairs now you should have taken some time to think about how to approach this idea of whether Holden or Ford owners *love* their cars more.
I've deliberately picked the word love as it's means different things to different people (and therefore you may have different ways of approaching your inquiry). This is fair too as Statisticians get paid to work for clients and sometimes those clients will ask for things that aren't too specific.
I'm expecting that you've began to give some definitions (spelling out exactly what you're doing). There are some key things to cover - who/what/where/when. I.e. if you data comes from Trademe Website - you need to state this. If you're looking at price there are several to go from (current bid, reserve price, buy now price, 'or nearest offer' price). You need to specify these - justify which one you're picking.
I'm also expecting that you've been looking at the data - how much is there? How many XR6's are advertised? Can you use all of these? If too many you will need to sample (pick a few) - how are you going to do this (spell it out in your presentation)?. How does this compare with the Commodores? Are all the XR6's the same (if not why not) - how are you accounting for these? This is an important aspect of the PPDAC cycle as if your data is bias from the start it will lead to bad conclusions.
You want to think about your overall presentation (I'm thinking most pairs will do a PowerPoint - but that is not necessary the case). Try to balance your time - don't get sucked into spending too much on making things pretty and sacrifice your actual processing time.
From here you should start to think about finding the measures of the middle (mean, median, mode) and the measures of spread (range, upper and lower quartiles).
PPDAC Inquiry In Pairs You have to come up with a logical approach and conclusion (using the PPDAC cycle) to the following idea...
I want to know if Holden Commodores or Ford XR6's are really loved more by their owners.
Problem (was given last post)
Plan - In your pairs you have to come up with some definitions...
How will you know you're comparing fairly (ie not all old Fords versus new Holdens)?
How will you quantify the "love" (this is possible to do sort of).
How will you find your data?
What will your data be (discrete/counted or continuous/measured)?
How many pieces of data will you need?
Data - One of the two of you will need to write down all of the data (probably in order), maybe rounded, perhaps using a table and or a stem n leaf graph.
Analysis - Finding the mean, median, mode, range, upper and lower quartiles. Doing some graphs - box n whiskers, maybe scatterplot, maybe bar graph.
Conclusion - you will need to make a presentation (poster or powerpoint) to the rest of the class which will answer whether owners love Holdens or Fords more.
Marks will be allocated for...
Communicating your thinking clearly (that you've appreciated that the results will vary).
Working well with your time (avoiding any last min rush jobs).
Presentation (make it good).
Use of the PPDAC headings in your presentation (see below for more hints).
Mistake free working (showing working out).
Teamwork (not just relying on one person).
Thinking outside the square (big picture ideas).
You will have four class periods in which you can do this inquiry project. Presentations will be on Friday 5th September.
The Range
The range is the most basic measure of the spread of data. It shows how consistent the data is.
When we look at the data from our dart throwing...
We can see that although Paea's average (aka mean) was the highest he was not consistent in his scores. The range is like the measure of consistency.
Technically the Range is = Highest minus Lowest.
In our data Baylees Range is 18 - 4 = 14, Jordan is 17 - 3 = 14, Paea is 60 - 5 = 55, Pierce is 14 - 5 = 9, Finn is 50 - 0 = 50 and Josh was 26 - 1 = 25.
A way of thinking about range is to think about a tank firing a shell.
The shell will go between the longest/greatest distance (several km) to it's shortest distance (about 50m). So the range is the difference between those two numbers (it's where the shell can land).
Quartiles
The second major measure of the spread of the data is to know about the Upper and Lower Quartiles. The names gives you the hint - quarters (25%).
To find the quartiles we have to...
Step One - Have the data all in order (lowest to highest).
Step Two - Find the halfway (median aka middle).
Step Three - Find the halfway of the bottom half of data (Lower Quartile).
Step Four - Find the halfway of the top half of the data (Upper Quartile).
Quartiles lead us into a major important graph called the Box and Whisker Graph. This is the A in PPDAC (the analysis).
Box n Whisker Graphs allow us to compare two similar pieces of data.
E.g. Holden Commodore vs Ford XR6's
Which Vehicle will last the longest before it's time to get rid of it?
PPDAC
P - Problem
P - Plan
D - Data
A - Analysis
C - Conclusion
What would be a good way to investigate which of these vehicles will last the longest before it's time to get rid of it?
Measures of a Spread
There are two main things we need to understand about comparing two things (using data). The middle we've covered (mean/median/mode). The spread is also very important.
e.g. Score from two players in darts (three darts each).
Here is a simulator that we want to get some scores (this we'll use as our data) from you guys for...
Summary of Learning We have now covered the following materials...
Data - numbers Counted Data - no decimals (aka discrete data) Measured Data - yes decimals (aka continuous data). Cleaning the Data - write it down (delete and replace later). Bias Data - incorrect by intent or accident (aka b.s. data). Inquiry Cycle - PPDAC (thinking about the logical approach to an investigation) Measure of the Middle - mean/median/mode Mean = total/#counted (divide because the teacher is "mean"). Median = Middle in order (think the eyes "i's"). Mode = Most common. Stem n Leaf Graph - shows all the data. (can be sorted or unsorted).
Stem and Leaf and Middle Measures.
Today we're going to get into the basics of finding the middle of any data set.
For this lesson we're going to look at counted data (discrete).
Here is a copy of the power point of notes.
The key learning [WALT] is to know the three measures of the middle. And to also know what a "Stem and Leaf" graph looks like.
Here is the idea of stem and leaf...
you can see the stem up the middle (getting bigger and bigger) and the leaves coming off the sides (extension work is the idea of both sides coming off the middle numbers).
This is what they look like in maths...
The practice work is in the text book on pages 407 to 409 Exercise 28.7.
here is an online video for these stem and leaf plot (you need head phones for this)...
The Great Lake Fishing Competition One of the very best weekends you can have fishing is an annual Trout fishing competition on Lake Taupo. It is called the "Open Trout Tournament" - anyone can enter.
Today we're going to do our own fishing - I will bring along Lake Taupo in a can. There are literally thousands and thousands of fish in the lake/can. Each of you will *catch* a pinch full of some fish (some will catch more than others). You can find your own fishing spot (in the can) and fish there. Then we'll find out some results. There will be a prize for the best table/boat (the biggest fish and the biggest average).
The learning today is about Samples. A sample is technically a small part/subset of the population. Our sampling is random. Random means that every fish in the can has an equal chance of being caught. We have to shake the can each pick to better ensure it's random.
We are going to need a way of recording down our results for each boat. For this we need to have a grouped frequency table.
Unit Plan Here are the two main planning documents. The first one is the Statistics Unit in a way students can read it (a copy will be given to you to cellotape in your books). The second one is my general order of teaching.
Statistical Inquiry Cycle A very common thing for all people to know is how to compare groups. If I said which fish is bigger, snapper from Waihi or snapper from Whitianga? I would expect you to approach the problem in a systematic way.
We call this the "Statistical Inquiry Cycle" and it's summed up in the acronym PPDAC [you absolutely must learn this]. It is a way of approaching the answer correctly.
In statistics there rarely is the right answer. Say if we said the that average year 9 at Waihi College weighed 53.4kg. It would be very unlikely that the a randomly selected student would actually weigh 53.4kg.
PPDAC stands for...
P roblem
P lan
D ata
A nalysis
C onclusion
Here is the summary poster that shows how PPDAC is a cycle that repeats upon itself.It was invented by Auckland University Statistics Department and is the cornerstone of NCEA Stats - you can get about 50 NCEA credits directly from being good at PPDAC.
I'm expecting that you've began to give some definitions (spelling out exactly what you're doing). There are some key things to cover - who/what/where/when. I.e. if you data comes from Trademe Website - you need to state this. If you're looking at price there are several to go from (current bid, reserve price, buy now price, 'or nearest offer' price). You need to specify these - justify which one you're picking. 
I'm also expecting that you've been looking at the data - how much is there? How many XR6's are advertised? Can you use all of these? If too many you will need to sample (pick a few) - how are you going to do this (spell it out in your presentation)?. How does this compare with the Commodores? Are all the XR6's the same (if not why not) - how are you accounting for these? This is an important aspect of the PPDAC cycle as if your data is bias from the start it will lead to bad conclusions. 
Quartiles lead us into a major important graph called the Box and Whisker Graph. This is the A in PPDAC (the analysis). 
Today we're going to do our own fishing - I will bring along Lake Taupo in a can. There are literally thousands and thousands of fish in the lake/can. Each of you will *catch* a pinch full of some fish (some will catch more than others). You can find your own fishing spot (in the can) and fish there. Then we'll find out some results. There will be a prize for the best table/boat (the biggest fish and the biggest average). 
A very common thing for all people to know is how to compare groups. If I said which fish is bigger, snapper from Waihi or snapper from Whitianga? I would expect you to approach the problem in a systematic way. 
