Introduction to Statistics Mr. Joseph Najuch Introduction to statistical concepts including descriptive statistics, basic probability rules, conditional probability, probability distributions, estimation of parameters, hypothesis testing using one or two samples, correlation and regression. Computer applications and simulations are done using MS EXCEL and TI-84 Graphing Calculators. 1

In your own words….. Define what you believe statistics means… 2

Why study statistics? Understanding statistics will…… Provide tools to analyze media reports - Presidential approval rating Help make investment decisions -1 year vs. 5 year performance Conduct research on major purchases -Consumer Reports on Dyson vacuum Do your own research and make conclusions 3

"Who do you think has the better ideas for strengthening the nation's economy: Barack Obama or John McCain?" -Obama 45% -McCain 28% -Both Equally 8% -Neither 11% -Unsure 8% Info from: Los Angeles Times/Bloomberg Poll. Aug , N=1,248 registered voters nationwide. MoE ± 3. 4

Definitions Statistics – is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. Data – are a fact or information coming from observations or counts, used to draw a conclusion or make a decision. It can be numerical or non-numerical. 5

Definitions Population – the group being studied (N) Sample – a subset of the population (n) Descriptive Statistics – organizing and summarizing the information collected (describe information in the form of charts, graphs, ect.) Inferential statistics – takes the results from the sample and extends to the whole population 6

Definitions Qualitative Data: Deals with descriptions. Data can be observed but not measured. Colors, textures, smells, tastes, appearance, beauty, etc. Qualitative → Quality Quantitative Data : Deals with numbers. Data which can be measured. Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages, Quantitative → Quantity 7

Univariate Data Bivariate Data Involving a single variableInvolving two variables - Does not deal with causes or relationships -Deals with causes or relationships The major purpose of univariate analysis is to describe stats. The major purpose of bivariate analysis is to explain the reason for the results. *central tendency - mean, mode, median *dispersion - range, variance, max, min, *quartiles, standard deviation. frequency *distributions bar graph, histogram, pie chart, line graph, box-and-whisker plot *analysis of two variables *simultaneously correlations comparisons, relationships, causes, explanations *tables where one variable is contingent on the values of the other variable. *independent and dependent variables Sample question: How many of the students in the freshman class are female? Sample question: Is there a relationship between the number of females in Computer Programming and their scores in Mathematics?

Data Classification (Types) There are four Levels of Measurement: Nominal Ordinal Interval Ratio * Be sure to understand the difference between each. (p. 14)