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Developing A Thesis

Developing A Thesis. Chapter 2.1 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U. What is a Thesis (Statement)?. A statistical thesis is an intellectual proposition (Wikipedia, 2004). in essence it is an idea

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Developing A Thesis

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  1. Developing A Thesis Chapter 2.1 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U

  2. What is a Thesis (Statement)? • A statistical thesis is an intellectual proposition (Wikipedia, 2004). • in essence it is an idea • there are other definitions as well – it is also a major research publication created by post-secondary students • you will develop a thesis for the course culminating project

  3. and… • a thesis is a formal statement or question that research will answer or discuss • when choosing a thesis… • can you state a specific question? • what are the main variables? • can these be measured statistically? • is there enough data to make interesting analysis? • is the topic manageable?

  4. Variables • a variable is a measurable characteristic that can change • variables can be continuous or discrete, containing nominal, ordinal, interval or ratio data • identifying the variables involved in a study is a significant task

  5. Brainstorming… • sometimes developing ideas is quite difficult • mind maps or concept maps are useful tools for this process

  6. Culminating Project • your first job is to choose a topic that is neither too simple nor too difficult • a project that is too large can be made more specific to reduce the size • once you have a topic you need to develop a thesis – a specific question or idea • without a specific question, the rest of the project will be more difficult

  7. Sample Hypotheses • There will be a positive correlation between the number of cigarettes smoked and the incidence of lung cancer • A woman’s level of education will be negatively correlated with the number of children

  8. Examples of projects… • Look at some examples of projects from other schools to give you an idea of where we are going • Your project will be produced electronically using a word processor as well as analysis software (Fathom or Excel) • A presentation using Microsoft PowerPoint is also required

  9. Exercises • try page 81 #1 a c e, 2 a c e, 4, 5, 13 • Tomorrow – Unit 3 Asgt • Mon – 2.5/2.6 • Tue – 2.7 • Wed – Review / Asgt Due • Thurs – Unit 3 Test

  10. Indexes • an index is number arbitrarily chosen to represent some data • the consumer price index is an example • http://www.statcan.ca/english/Subjects/Cpi/cpi-en.htm • what type of data would the consumer price index be? • interval

  11. Consumer Price Index (CPI) • A statistical measure of a weighted average of prices of a specified set of goods and services purchased by wage earners in urban areas • A price index which tracks the prices of a specified set of consumer goods and services, providing a measure of inflation • Factors include: gasoline, the purchase and leasing of automotive vehicles, homeowners' replacement cost and natural gas

  12. Characteristics of Data Chapter 2.2 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U

  13. What is data? • Data - a group of facts or information that is collected • Population - the group of individuals that a study is concerned with • e.g., if we want to find the opinions of students at CPHS, the population is all students at CPHS • This does not mean we collect data from every student!

  14. More Data Classifications • Quantitative data • data that can be measured numerically • ex: height or weight • Qualitative data • non-numerical data • Ex: marital status, eye color, attitudes • Time series data • data collected repeatedly over a long period of time

  15. Sampling • It is usually too expensive and/or time-consuming to collect data from the entire population (conduct a census) • A sample is a part of the population that is chosen to represent the population • If the sample is representative, then it provides an accurate picture of the entire population • Choosing the sample randomly avoids bias and yields a representative sample • A conclusion drawn from sample data is called an inference (we are assuming that the sample represents the entire population)

  16. Types of Studies • Cross sectional • A study which samples different groups of a population at the same time • e.g., sampling students in every grade from 9 through 12 at CPHS on one day • Longitudinal • A study which samples the same individuals over time • e.g., Sampling the class of 2013 (this year’s grade 9s) every year for 4 years • What are the advantages of each of these?

  17. Example • Which type of study is best for the following situations: cross-sectional or longitudinal? a) Determining what percent of high school students plan to attend university within 3 years? b) Determining the effect of a new pesticide on the growth of tomato plants? c) Testing the effectiveness of a new allergy medication? d) Predicting the results a month before an election?

  18. MSIP / Homework • Read Ex.1 to 3 on pp. 86 - 89 • Complete p. 89 # 1-6 and 10

  19. References • Wikipedia (2004). Online Encyclopedia. Retrieved September 1, 2004 from http://en.wikipedia.org/wiki/Main_Page

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