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Understanding Thesis Development and Data Management in Statistical Research

This resource outlines the fundamentals of thesis development, focusing on forming a precise research question and managing data effectively. It discusses the importance of variables, their classification, and appropriate methodology for sampling. The content highlights the significance of choosing the right topic for a culminating project and provides insights into statistical hypotheses. Additionally, it explains types of data, sampling techniques, and study designs, such as cross-sectional and longitudinal studies, aiding students in mastering data analysis and research organization.

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Understanding Thesis Development and Data Management in Statistical Research

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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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