Presentation on theme: "Sampling Lesson Objectives Key Words"— Presentation transcript:
1Sampling Lesson Objectives Key Words To understand different methods of sampling and sample sizeTo identify which sampling method to use to solve a problemKey Wordspopulationsamplerandomstratifiedbias
2Think back to last lesson Think back to last lesson. What problems did you have sorting through the data?
3We can’t possibly use all the data. We need to cut down the data we use. But we need to do this fairly.In analysing statistics we usually use a sample of the data.
4CensusCensus research uses data from every single member of the population.If we wanted to do a census study of Emmanuel students’ eating habits, we would have to ask EVERY child in the school.
5Census Advantages Disadvantages Very accurate and reliable data. Costs a lot of time and money.Very difficult to get data for absolutely everybody.
6Random SamplingA random sample uses data taken from some of the population chosen randomly – every member of the population has the same chance of being chosen.If we wanted to take a random sample of Emmanuel students’, we could put all the names in a list and then pick every tenth child to take data from.
7Random Sample Example: For this random sample I put all the names in alphabetical order and then chose every second child, either all the whites or all the yellows.Example:KayseyAbbottDanielHazledineRuthMerryweatherOliverBootSarahHopkinsHayleyRaynerJackBuckleyHollyHullandHannahRodgerTerri-LeeChristopherIsaacJessicaRyderAllistairBurton-CaseyBenLaneKieranTetleyEbonyChambersWilliamLeonardRhianThomasJoshuaCoatesColetteLevertonRebeccaVoceDurnerNicholasLewinLauraWantShannenFretwellRossLigginsIainWattJoelGeorgeMarriottAndrewWinterJamesGreenhalghWakasMasood
8Random Sample Advantages Disadvantages Data is unbiased and reliable. Some important parts of the population might be missed out.
9Stratified SampleA stratified sample divides the population into categories and then a random sample can be taken from each category. The number from each category represents the proportion of the population in that category.If we wanted to take a stratified sample of Emmanuel students’, we could group the children into male and female and year groups and then take a sample from each group.
10Stratified Sample Example: 1001 - 1004 1005 - 1008 For this stratified sample I’m going to group the students based on birth year and sex first. We choose at random from each group based on the group’s size.Example:MaleFemaleChris Isaac, Will Leonard, Andrew Winter, Joel George, James Greenhalgh, Daniel Hazeldine, Kieran Tetley, Oliver BootTotal of 8 people we use 4Terri-Lee Buckley, Sarah Hopkins, Jessica Ryder, Colette Leverton, Kaysey Abbot, Hayley Rayner, Shannen Fretwell, Ruth MerryweatherJack Buckley, Alistair Burton-Casey, Josh Coates, Oliver Durner, Ben Lane, Nick Lewin, Ross Liggins, Jack Marriott, Wakas Masood, Iain WattTotal of 10 people we use 5Ebony Chambers, Holly Hulland, Hannah Rodger, Rhian Thomas, Rebecca Voce, Laura WantTotal of 6 people we use 3
11Stratified Sample Advantages Disadvantages Ensures that members of all parts of the population are considered.More time-consuming and expensive than a random sample.
12Sample sizeBefore we take a sample of the population, we must consider how large the sample should be.Large samples are more likely to be accurate and representative.But, larger samples take longer to sort and may be more expensive to collect.
13Activities Read through the excellent examples on page 33 and 34. Try questions 1, 4 and 5.
14“People in Europe live longer than people in Africa.” HomeworkFor the first part of your Statistics coursework you will need to test the hypothesis:“People in Europe live longer than people in Africa.”Think about how we could use what we’ve learnt about sampling to help this investigation – answer the questions on the worksheet.