• 2 Chi-square (χ ) test of significance • 2 Chi-square (χ ) test of significance was designed by Karl Pearson (1899). • This test is applied to test the hypothesis when observations are expressed only in frequency. • Chi-square is the sum of the ratio of square deviation ...
Why Statistical Significance Test • Suppose we have developed an EC algorithm A • We want to compare with another EC algorithm B • Both algorithms are stochastic • How can we be sure that A is better than B? • Assume we run A and B once, and get ...
A significance test is a formal procedure for comparing observed data with a claim (hypothesis). Significance The claim is a statement about a parameter. Test Tests ask if sample data give good evidence against a claim. If an observed statistic is “far” away from a hypothesized claim about a ...
What test should you use? First, what type of data do you have? Examples of Continuous Data Examples of Discrete Data (can (can’t be counted) be counted) • Fluorescence Intensity • Sides on a dice • Protein Concentration • Number of melanosomes in a • Cell Size melanocyte Most ...
Allowing [statistical software] to do our thinking is a sure recipe for disaster. (Good & Hardin, 2012, p. xi) - or did it really? «Simple» statistical tests • 2 chi-square (X ) test • t-test - or did it really? Statistical hypothesis testing 1. Formulate a hypothesis E ...
Learning Objectives By the end of this lecture, you should be able to: – List the basic steps in a hypothesis test – Describe what is meant by a p-value – Take a p-value and say whether the result is statistically significant, and therefore, whether we reject or fail to ...
Section 7.1 Objectives • A practical introduction to hypothesis tests • How to state a null hypothesis and an alternative hypothesis • How to Identify type I and type II errors and interpret the level of significance • How to know whether to use a one-tailed or two- tailed ...
Hypothesis Testing Introduction • In this session we will see • What a hypothesis test is • What a p-value is • What a t-test is • This is intented for first stages in Statistics Students • Previous knowledge: descriptive statistics, random variables, distributions Hypothesis Testing What is a hypothesis ...
(8.1) Definition: A statistical hypothesis is a statement concerning one population or more. 8.1.1 The Null and The Alternative Hypotheses: The structure of hypothesis testing will be formulated with the use of the term null hypothesis. This refers to any hypothesis we wish to test that called ...
About the Session: ‘Evidence interpretation’ questions form 10% of AKT marks RCGP also refers to this section as: ‘research and statistics’ and ‘critical appraisal and evidence based clinical practice’ Topics covered in today's presentation: Clinical testing/contingency tables Clinical study types and interpretation of results Significance testing ...
Hypothesis Tests Parametric Tests - tests about specific 2 population parameters (μ, σ , etc.) –Is μ different from a predetermined 1 value? –Is μ different from μ ? 1 2 Non-Parametric Tests - tests about the shape of the population (medians?) –Is this population different from ...
Types of Statistics/Analyses DESCRIPTIVE STATISTICS INFERENTIAL STATISTICS Frequencies Hypothesis Testing Correlation Basic measurements Confidence Intervals Descriptive Statistics describe Significance Testing a phenomena Prediction How many? How much? Inferential statistics make Inferences about a phenomena BP, HR, BMI, IQ, etc. Proving or disproving theories Associations between phenomena If sample relates to ...
Historical Aspect • The term statistical significance was coined by Ronald Fisher(1890-1962). • Student t-test : William Sealy Gosset. 2 Basis of Statistical Inference Statistical inference (a conclusion reached on the basis of evidence and reasoning) is the branch of statistics which is concerned with using probability concept to deal ...
Course topics : (0.8 ECTS-eight hours) 2 Generating Hypothesis (lecture 2) Null Hypothesis (H0) Experimental = Control or Science is all about Experimental – Control = 0 Falsification and not confirmation e.g. Alternative Hypothesis (HA) Coffee Experimental != Control smoking or Pancreatic cancer Experimental – Control != ...
Syllabus 1. Use of Data in Geography: Geographical Data Matrix, Significance of Statistical Methods in Geography; Sources of Data, Scales of Measurement (Nominal, Ordinal, Interval, Ratio). 2. Tabulation and Descriptive Statistics: Frequencies - Deciles, Quartiles, Percentile, Cross Tabulation. 3. Measurement of Central Tendencies: Mean, Median and Mode, Centro-graphic Techniques. 4 ...
PPT - Power Point | 0.77 MB | Free Download
