Lecture One

6 Pages
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Department
Management and Organizational Studies
Course Code
Management and Organizational Studies 2242A/B
Professor
Drewes

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Description
Lecture One: Use whichever textbook you’d like – the third edition has rock, paper, scissors on the cover and you’d be able to find used much easier. So that. Why study stats? Stats techniques are used to make business decisions Economists need to test theories We need to estimate magnitudes of important economic parameters (Marginal propensity to consume, price elasticity of demand for oil, etc) Statistics is… He didn’t care about this slide because he said it made it sound like he was going to take over the world with stats Descriptive stats Methods of organising, summarising and presenting data in an informative way Frequency distribution, chart forms, central tendency measures, data clustering “This was this” Inferential stats Methods used to determine something about a population, based on a sample Population is the entire set of people or objects of interest or the measurements obtained A sample is a portion, or part, of the population interest We use samples so we don’t break everything or spend entirely too much money (i.e. if you want to figure out how many of a certain car will survive a crash, you don’t drive all of them into a wall) Basically, we make guesses about things based on the data we bring in “We estimate this was this based on this” Why sample? Prohibitive cost of surveying the whole population Destructive nature of some tests Physical impossibility of capturing the possibility Sampling error is why we have this course Your sample mean won’t be the true one. Your answer won’t be accurate unless you’re lucky During tests you’re only responsible for things we lecture on Chapter two Frequency distribution A grouping of data into mutually exclusive classes showing the number of observations in each class Relative frequency distribution Class frequencies can be converted to relative class frequencies to show the fraction of the total number of observations in each class (most people find relative frequencies to be more informative – if you’re looking at houses, it makes more sense to know that 47% of houses sold were a certain type, rather than the pure number) Bar Charts The horizontal axis shows the variable of interest and the vertical axis the amount, number or fraction of each of the possible outcomes A distinguishing characteristic of a bar chart is that there is a gap between bars (Histograms don’t have that, which is the only difference between them. Stats people are anal, apparently) Can depict any level of measurement – nominal, ordinal, interval, ratio You can create bar charts in excel – instructions for that are in the textbook if you don’t know how to do that. Lovely Quantitative data Decide of the number of classes Determine class interval or width (must be equal!) Let’s create intervals of 10% for classes because that’s natural and 1% is stupid. Set the individual class limits Tally the list prices into the classes Count the number of items in each class (One of the assignments is to look at marks for this class for last year) Frequently used terms Class midpoint: point between lower and upper limit Class interval: subtract the lower limit of the class from the upper limit and get something I missed in the slide. Yay me Example of descriptive things` Report on 96 homes in the south east region. You take the lowest and highest, because they`re important. 1. Sort data, lowest to highest. 2. Jay and I were talking so I missed this. 3. But it’s in the slides. Sorry Katey and future self. 4. Tally homes 5. Count the tallies. And you have a frequency distribution. (“And you thought stats was going to be hard. Haha.”) 6. You can make a relative frequency by dividing each frequency by the total number of terms. (If you then go through and add the first to the second, then the third to that, you get a cumulative frequency distribution and that tells you what percentage are below a certain level) He put up a slide of formulas of craziness to say we don`t need to memorise formulas and during tests he will give us a formula sheet. Yay him. You try it! I didn’t want to try. Relative frequency distribution We already covered this, so he basically ignored it. Most people find this more informative. So there’s that. Histogram characteristics Similar to the bar chart (doesn’t have gaps) We’re not going to be fussy about this Won’t have to do histograms in excel Excel - Options - Addins - Manage options - Excel toolpack Chapter Three The next step in summarising data – we took 100 numbers and smashed it into 5 numbers, but we’re going to get one number here. Do you want to know how students did in a class? Ask the average. We are going to learn to spell Chebyshev. That’s what this chapter is. Yay us. Measures of location Arithmetic mean Weighted mean Median Mode Geometri
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