PPDAC Cycle.

Slides:



Advertisements
Similar presentations
Statistics – Bivariate
Advertisements

Analyzing Data (C2-5 BVD) C2-4: Categorical and Quantitative Data.
Are our results reliable enough to support a conclusion?
Wf Statistical Coursework There are more vowels used in a page written out in French rather than English. Girls are better at maths than boys.
Jared Hockly - Western Springs College
PROBLEM This is where you decide what you would like more information on. PLAN You need to know what you will measure and how you will do it. What data.
Making the call Year 10 Some activities to immerse students in ideas about sample, population, sampling variability and how to make a “claim” when comparing.
Analysis. Start with describing the features you see in the data.
The controlled assessment is worth 25% of the GCSE The project has three stages; 1. Planning 2. Collecting, processing and representing data 3. Interpreting.
“Teach A Level Maths” Statistics 1
Interpreting data … Drawing and comparing Box and Whisker diagrams (Box plots)
Level 1 Multivariate Unit
Analyzing Data Sets For One Variable
Investigations into Mathematics: Survey Project Number of Siblings Daniel Ballew October 8, 2010.
Statistics: Use Graphs to Show Data Box Plots.
Meet the Kiwis…. Population of kiwis… Codes… Species Region GS-Great Spotted, NIBr-NorthIsland Brown, Tok-Southern Tokoeka NWN-North West Nelson, CW-Central.
Information for teachers This PowerPoint presentation gives some examples of analysis statements. Students own answers will differ based on their choice.
Answering questions about life with statistics ! The results of many investigations in biology are collected as numbers known as _____________________.
Mayfield – Data Handling Lo: To understand which is the appropriate graph to test each hypothesis. To be able to self analyse and adapt my own work.
3. Use the data below to make a stem-and-leaf plot.
Informal statistical inference: Years 10 to 12 Maxine Pfannkuch and Chris Wild The University of Auckland.
Report Exemplar. Step 1: Purpose State the purpose of your investigation. Pose an appropriate comparison investigative question and do not forget to include.
90288 – Select a Sample and Make Inferences from Data The Mayor’s Claim.
Measures of central tendency are statistics that express the most typical or average scores in a distribution These measures are: The Mode The Median.
Warm Up Find the mean, median, mode, range, and outliers of the following data. 11, 7, 2, 7, 6, 12, 9, 10, 8, 6, 4, 8, 8, 7, 4, 7, 8, 8, 6, 5, 9 How does.
Measures of Center vs Measures of Spread
Plan and Data. Are you aware of concepts such as sample, population, sample distribution, population distribution, sampling variability?
Carrying out a statistics investigation. A process.
 The mean is typically what is meant by the word “average.” The mean is perhaps the most common measure of central tendency.  The sample mean is written.
Stage 1 Statistics students from Auckland university Using a sample to make a point estimate.
{ Box-and-Whisker Plots. Median, Quartiles, Inter-Quartile Range and Box Plots. Measures of Spread The range is not a good measure of spread because one.
Understanding Numerical Data. Statistics Statistics is a tool used to answer general questions on the basis of a limited amount of specific data. Statistics.
Stage 1 Statistics students from Auckland university Sampling variability & the effect of sample size.
PPDAC Cycle.
I wonder if right handed students from the CensusAtSchool NZ 2009 Database are taller than left handed students from the CensusAtSchool NZ 2009 Database.
2-6 Box-and-Whisker Plots Indicator  D1 Read, create, and interpret box-and whisker plots Page
Use statistical methods to make an inference. Michelle Dalrymple.
Single middle value The Median The median is the middle value of a set of data once the data has been ordered. Example 1. Robert hit 11 balls at Grimsby.
Problem I wonder if year 9 students from the censusatschool 2011 database have longer travel times from home to school than year 13 students from the.
Statistical Thinking Julia Horring & Pip Arnold TEAM Solutions University of Auckland.
CHAPTER 11 Mean and Standard Deviation. BOX AND WHISKER PLOTS  Worksheet on Interpreting and making a box and whisker plot in the calculator.
KIWI KAPERS Species Weight(kg)Height (cm) Region/Gender.
 NHANES 1000, MARIJANA USE  COMPARE WHAT HAPPENS WHEN WE CHANGE SAMPLE SIZE CENSUS AT SCHOOL, ARM SPAN LOOKING AT WHAT HAPPENS TO THE SAMPLING.
Box and Whiskers Plots (Box Plots)..\..\..\..\Program Files\Pearson Prentice Hall\Lesson PowerPoint\PH Pre-Algebra 2009 Lesson PowerPoint\PH Pre-Algebra.
MM2D1: Using sample data, students will make informal inferences about population means and standard deviations b. Understand and calculate the means and.
Multi-variate data internal 4 Credits. achieved The student: Poses an appropriate comparison question, with or without guidance from the teacher,
Topic 4:Statistics Learning Intention: to solve a statistics problem using the PPDAC enquiry cycle. To classify data as discrete or Continuous. Success.
Recapping: Distribution of data.
4. Interpreting sets of data
A statistical investigation
Inference.
An Introduction to Statistics
Chapter 6.4 Box and Whisker Plots
Do the lengths of the object you are measuring or the tool you choose to measure with affect how precise your measurement is likely to be?  In this section,
Box and Whisker Plots.
11.2 box and whisker plots.
Inferences to the population
Displaying Distributions with Graphs
Inference credits Making the call……..
Statistics: The Interpretation of Data
“Teach A Level Maths” Statistics 1
“Teach A Level Maths” Statistics 1
Selecting a Sample Notes
(-4)*(-7)= Agenda Bell Ringer Bell Ringer
Chapter 6.4 Box and Whisker Plots
Dot plots show how data is distributed (spread out)
13E – comparing data sets.
Statistics – Bivariate
Gaining Achieved.
Samples & Populations 2.1 Learning Target: Analyze a sampling plan to make inferences about a population. Homework: Complete class work on p. 2-3.
Presentation transcript:

PPDAC Cycle

What is the PPDAC cycle? The PPDAC cycle is a way of answering statistics questions. Each letter stands for one step. P = D = A = C = Problem Plan Data Analysis Conclusions / Comments

Problem To use the PPDAC cycle you need to state a problem or question. A suitable problem needs: to be answerable with the data obtained, It is clear who the problem is about. We know what numbers we need

Examples of summary questions. I wonder what are the typical heights of Year12 students at HGHS in 2013. I wonder what are the typical number of people in the house for Year12 students at HGHS in 2013. Examples of comparison questions. I wonder if Year 12 students at HGHS in 2013 tend to have a larger neck circumference than Year 10 students at HGHS in 2013.

Plan You need to show a clear explanation of why the particular sampling method has been chosen Sampling method means how you chose the people to measure.

For example: I have chosen to take a simple random sample For example: I have chosen to take a simple random sample. I have taken my random sample by drawing name cards out of a bag. This method will provide me with a sample of heights where every Year 12 student at this school had an equal chance of being selected. The sample should therefore be representative of all the Year12 students at this school.

Data Choose at least 30 from each group.

For example: The student has listed the 30 students they selected from all the Year12 students. They have included all of the variables available.

Analysis Draw dot plots or stem and leaf tables to organise the data. Draw box and whisker graphs if you need to compare groups. Use SSUMO to analyse the graphs.

First draw a dot plot to give a very simple overview of the data First draw a dot plot to give a very simple overview of the data. From this graph features such as the shape or distribution of the data can be described. Also comments about spread, the middle group (or groups) and anything unusual can be noted. A box plot visually gives more information especially in comparison situations. The box plot gives a good indication of the range, the inter-quartile range and where the middle 50% (box) of the data lies. It is recommended that the associated dot plot is kept with the box plot.

Conclusions / Comments Your conclusion must answer the problem. Re-write your problem as an answer.

e.g. Based on these data it seems that Year 10 boys were on average taller than the Year 10 girls. The median height and mean height for the boys was 170 cm compared with the median height and mean height for girls of 164 cm. This suggests that boys are on average about 6 cm taller than girls in Grade 10. There is a small amount of overlap between the middle 50% of height values. This small overlap supports the conclusion that boys are on average taller than girls. Also 75% of the boys are taller than 50% of the girls.

Extra Conclusions To write a better conclusion you may want to add extra information about: 1. Anything that might have gone wrong 2. Any way to improve your investigation. 3. Any extra information you got from your graphs.

e.g. From our sample we could not say that it was likely that boys in the 2011 censusatschool database had heavier schoolbags than girls in the 2011 censusatschool database. However the DBM was only 20grams below 1/3 of the OVS. To check our conclusion I would recommend that we take a larger sample of 100 students. This would mean there is less variability in the sample, because it is larger, and therefore our conclusion could be made more reliable. From my results It could be recommended that if the government makes bag weight limits they should be the same for boys and girls.