LEARNING OBJECTIVE: Use real life statistics as a persuasive device

Slides:



Advertisements
Similar presentations
The Scientific Method.
Advertisements

Ka-fu Wong © 2003 Chap 2-1 Dr. Ka-fu Wong ECON1003 Analysis of Economic Data.
Types of Formal Reports Chapter 14. Definition  Report is the term used for a group of documents that inform, analyze or recommend.  We will categorize.
Whiteboardmaths.com © 2009 All rights reserved
Data Management Grade 7. What’s the Story? Secondary data is information that was collected by someone else. Referring to information that was published.
The Writing Process Prewriting.
 Frequency Distribution is a statistical technique to explore the underlying patterns of raw data.  Preparing frequency distribution tables, we can.
Unit 18 Future trends. Objectives Focus Warm up 18.1 Making predictions 18.2 Talking about the future 18.3 Changing the way we work Sum-up Assignments.
Carrying out a statistics investigation. A process.
Experimental Design and Implementation Honors Biology.
© Hamilton Trust Keeping Up Term 3 Week 1 Day 2 Objective: Round decimals to the nearest whole number.
25th February 2016 Reptile Life Cycle
AP CSP: Cleaning Data & Creating Summary Tables
Identity Pack Session: You Can’t Judge a Book by Its Cover
Experimental Design Principles of Biomedical Science
Classroom Skill Building
WebQuest: Where you design your own Space Exploration Mission
As You Enter Take a moment to network and exchange contact information from those in the room you do not have yet.
Evaluation of Research Methods
Reading Focus: Use Details to Understand the Main Idea Close Reading
4. Finding the Average, Mode and Median
Literacy Research Memory Skill practice Challenge
Developing a Methodology
Water Design Challenge
The education and wealth of women in Collective Action groups
Designing Performance Assessments
Prepared Platform Speeches
Descriptive Statistics
WW7: Focus and Goals Focus:
Learning Objective: To assess my understanding of representing data
Inferential Statistics
Survey Says…… Unit 2 IB Project.
Transport Frequency Transport Frequency Transport Frequency
Classroom Skill Building
Mathematics Lesson 1: Handling Data – Bar Charts
Reading Objectives: Close Reading Analyze visuals. RI.4.7
Classroom Skill Building
Question to be debated here
Reading Objectives: Close Reading
Warm-up We are going to collect some data and determine if it is “normal” Roll each pair of dice 10 times and record the SUM of the two digits in your.
Conducting an experiment and collecting data using product testing
L.O. To identify and share the aspects of identity that have had the most impact n each of us TLN Identity Pack L5.
Change Proposal: When to Use It
Current Event Project Due by May 21st.
Water Design Challenge
Year 12 into 13 bridging work
Scientific Method The 7-step process to scientific investigations.
Effective Presentation
Interviewing techniques
Scientific Method The 8-Step Process to Scientific Investigations.
LI: I can use a scale to display data
Listening Lesson Spring 2018
Secure Knowledge (1-3) Describe investigation process
What Happened Long Ago? Year 1 History / Even Year.
Human Energy Systems Unit Activity 5.2 Carbon Emissions Jigsaw
Are You a Data Detective?
Place 3-digit numbers on a line
What is the question? The answer is -2
A survey about communities
Tuesday, February 2, :10 – 8:40.
Talking Rubbish LEARNING OBJECTIVE: To identify and understand elements of public speaking, with a specific focus on organising content in a coherent manner.
Reading Street Comprehension Skills: Author’s Purpose
Keep your scale in the sheet protector. You will only
Lesson 8: Analyze an Argument
Stage 6: Conducting market research
Add Details/Rewrite a Portion
Writing Algebraic Expressions
Steps of a Lesson – Wrap Up
Working Scientifically
Stage 3: Conducting market research
Presentation transcript:

LEARNING OBJECTIVE: Use real life statistics as a persuasive device PLASTIC PERSUASION LEARNING OBJECTIVE: Use real life statistics as a persuasive device

THE DIRTY DOZEN Almost a decade ago, Surfers Against Sewage conducted a Plastic Pollution Brand Survey; a brand audit that revealed that the majority of all beach litter (56%) was attributable to just twelve corporations, dubbed the ‘Dirty Dozen’. Talk in pairs, remember to prepare reasons for your answers. What might Surfers Against Sewage’s motive be for doing this survey? Can you suggest who the top culprits may be? How useful is this data now?

The Dirty Dozen Data No. of items Corporation Nestle 51 Coca Cola 49 Walkers/Frito Lays 47 Kraft 45 Tesco 34 Mars 22 Unilever 19 PepsiCo 16 United Biscuits 15 Carlsberg 13 Co-op 10 Asda 9 Corporation In your pairs, choose three of the following questions to discuss. If the litter pick had been repeated the following week would the data be the same or different? Why? Is the data reliable? Why? What story does the data tell us? How can this data be updated? How many items of litter were collected in total? What is the range of this data set?

QUESTION: If the survery was repeated today would the Dirty Dozen remain the same? WHY?

Plastic Pollution Brand Survey YOUR MISSION: Surfers Against Sewage are inviting you to conduct your very own Plastic Pollution Brand Survey ‘Wherever you are, and whether it’s a mountain or a river, in the city or by the sea, you can play a part. Let’s make the polluter pay!’ Find the new ‘Dirty Dozen!’ Arm yourself with statistics! Lead the change with some plastic persuasion!

Plan the pick! As a class, plan how you will collect your data. Where/when will you conduct your survey? For what duration? How will you record your findings? Will you do it more than once to observe differences? Why are you gathering this data? What purpose will it serve?

Data Collection: Tally Chart A tally chart to show the frequency of plastic litter found for each brand Item of plastic Brand Tally Frequency Bottle Revian 2 Wrapper Frankies 5 Example tally chart

Data Collection: Tally Chart A tally chart to show the TOTAL frequency of plastic litter found for each brand Item of plastic Brand Tally Frequency Collate class results. Of course, you may have collected items from more than 12 brands. Decide together if you will record or dismiss this data.

Data Collection: Pie Chart Brand No. of items (frequency) Angle (rounded to nearest whole number) Nestle 51 56˚ Coca Cola 49 53˚ Walkers/Frito Lays 47 Kraft 45 Tesco 34 Mars 22 Unilever 19 PepsiCo 16 United Biscuits 15 Carlsberg 13 Co-op 10 Asda 9 To draw a pie chart for the Dirty Dozen data Find total frequency = 330 Find proportion of total items for each brand Nestle 51 ÷ 330 x 360˚= 55.6˚ Coca Cola 49 ÷ 330 x 360˚ = 53.4˚ Choose a brand, tell your partner how you would calculate the proportion of the pie chart to allocate it.

Data Collection: Pie Chart A pie chart to show the frequency of plastic litter found for each brand: The Dirty Dozen Use one of the following phrases to make a statement about the data depicted. proportion approximately most common least common

Using the data collected in your brand survey, draw a pie chart. Our success criteria Success criteria could include, for example: Include a clear title Use a key to explain segments Be accurate to the nearest degree

QUESTION: Did the Dirty Dozen remain the same QUESTION: Did the Dirty Dozen remain the same? Are there any similarities? What are the key differences? What is the biggest surprise?

Plastic Pollution Brand Survey YOUR MISSION: Surfers Against Sewage are inviting you to conduct your very own Plastic Pollution Brand Survey ‘Wherever you are, and whether it’s a mountain or a river, in the city or by the sea, you can play a part. Let’s make the polluter pay!’ Find the new ‘Dirty Dozen!’ Arm yourself with statistics! Lead the change with some plastic persuasion!

CHALLENGE: Numbers are power CHALLENGE: Numbers are power. Use them to PERSUADE a brand to make a change.

Brainstorm key features of a persuasive text

Brainstorm appropriate language and phrases