Using the T-test IB Biology Topic 1.

Slides:



Advertisements
Similar presentations
TWO STEP EQUATIONS 1. SOLVE FOR X 2. DO THE ADDITION STEP FIRST
Advertisements

/ /17 32/ / /
Introductory Mathematics & Statistics for Business
STATISTICS INTERVAL ESTIMATION Professor Ke-Sheng Cheng Department of Bioenvironmental Systems Engineering National Taiwan University.
Whiteboardmaths.com © 2004 All rights reserved
1 2 Test for Independence 2 Test for Independence.
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
Jeopardy Q 1 Q 6 Q 11 Q 16 Q 21 Q 2 Q 7 Q 12 Q 17 Q 22 Q 3 Q 8 Q 13
0 - 0.
MULTIPLICATION EQUATIONS 1. SOLVE FOR X 3. WHAT EVER YOU DO TO ONE SIDE YOU HAVE TO DO TO THE OTHER 2. DIVIDE BY THE NUMBER IN FRONT OF THE VARIABLE.
Addition Facts
Summative Math Test Algebra (28%) Geometry (29%)
Your lecturer and course convener
Lecture 2 ANALYSIS OF VARIANCE: AN INTRODUCTION
CS1512 Foundations of Computing Science 2 Lecture 20 Probability and statistics (2) © J R W Hunter,
1 Contact details Colin Gray Room S16 (occasionally) address: Telephone: (27) 2233 Dont hesitate to get in touch.
1 Session 8 Tests of Hypotheses. 2 By the end of this session, you will be able to set up, conduct and interpret results from a test of hypothesis concerning.
Box and Whiskers with Outliers. Outlier…… An extremely high or an extremely low value in the data set when compared with the rest of the values. The IQR.
Biostatistics Unit 5 Samples Needs to be completed. 12/24/13.
You will need Your text Your calculator
Department of Engineering Management, Information and Systems
The t-distribution William Gosset lived from 1876 to 1937 Gosset invented the t -test to handle small samples for quality control in brewing. He wrote.
(This presentation may be used for instructional purposes)
Non-Parametric Statistics
5-1 Chapter 5 Theory & Problems of Probability & Statistics Murray R. Spiegel Sampling Theory.
Area Of Shapes. 8cm 2cm 5cm 3cm A1 A2 16m 12m 10m 12cm 7cm.
Measures of Central Tendency and Dispersion
Hypothesis Tests: Two Independent Samples
Hours Listening To Music In A Week! David Burgueño, Nestor Garcia, Rodrigo Martinez.
Quantitative Analysis (Statistics Week 8)
Partly based on material by Sherry O’Sullivan
Lets play bingo!!. Calculate: MEAN Calculate: MEDIAN
Chapter 15 ANOVA.
Module 16: One-sample t-tests and Confidence Intervals
Addition 1’s to 20.
Mode, Median and Mean Great Marlow School Mathematics Department.
25 seconds left…...
Chi-square and F Distributions
Arithmetic of random variables: adding constants to random variables, multiplying random variables by constants, and adding two random variables together.
Statistical Inferences Based on Two Samples
© The McGraw-Hill Companies, Inc., Chapter 10 Testing the Difference between Means and Variances.
Evaluation of precision and accuracy of a measurement
Measures of Dispersion. Here are two sets to look at A = {1,2,3,4,5,6,7} B = {8,9,10,11,12,13,14} Do you expect the sets to have the same means? Median?
Ch 14 實習(2).
PSSA Preparation.
Experimental Design and Analysis of Variance
CHAPTER 14: Confidence Intervals: The Basics
Multiple Regression and Model Building
Area Of Shapes. 8cm 2cm 5cm 3cm A1 A2 16m 12m 10m 12cm 7cm.
Finding the Mean & the Standard Deviation. Finding the mean & Standard Deviation Find the Mean and the Standard Deviation of 6,5,5,4,5,5,6,5 and 4 We.
Session 6: Basic Statistics Part 1 (and how not to be frightened by the word) Prof Neville Yeomans Director of Research, Austin LifeSciences.
Are our results reliable enough to support a conclusion?
Review Feb Adapted from: Taylor, S. (2009). Statistical Analysis. Taken from:
Answering questions about life with statistics ! The results of many investigations in biology are collected as numbers known as _____________________.
Topic 1: Statistical Analysis
Statistics The POWER of Data. Statistics: Definition Statistics is the mathematics of the collection, organization, and interpretation of numerical data.
Statistical Analysis Mean, Standard deviation, Standard deviation of the sample means, t-test.
Statistical Analysis IB Topic 1. Why study statistics?  Scientists use the scientific method when designing experiments  Observations and experiments.
Are our results reliable enough to support a conclusion?
The T-Test Are our results reliable enough to support a conclusion?
Using the T-test Topic 1.
Are our results reliable enough to support a conclusion?
Statistics.
Are our results reliable enough to support a conclusion?
Are our results reliable enough to support a conclusion?
Are our results reliable enough to support a conclusion?
Facts from figures Having obtained the results of an investigation, a scientist is faced with the prospect of trying to interpret them. In some cases the.
Statistical analysis.
Are our results reliable enough to support a conclusion?
Are our results reliable enough to support a conclusion?
Presentation transcript:

Using the T-test IB Biology Topic 1

Are our results reliable enough to support a conclusion?

Imagine we chose two children at random from two class rooms… … and compare their height …

… we find that one pupil is taller than the other C1 … we find that one pupil is taller than the other WHY?

REASON 1: There is a significant difference between the two groups, so pupils in C1 are taller than pupils in D8 D8 C1 YEAR 7 YEAR 11

REASON 2: By chance, we picked a short pupil from D8 and a tall one from C1 D8 C1 TITCH (Year 9) HAGRID (Year 9)

How do we decide which reason is most likely? MEASURE MORE STUDENTS!!!

… the average or mean height of the two groups should be very… If there is a significant difference between the two groups… D8 C1 … the average or mean height of the two groups should be very… … DIFFERENT

… the average or mean height of the two groups should be very… If there is no significant difference between the two groups… D8 C1 … the average or mean height of the two groups should be very… … SIMILAR

Living things normally show a lot of variation, so… Remember:

It is VERY unlikely that the mean height of our two samples will be exactly the same C1 Sample Average height = 162 cm D8 Sample Average height = 168 cm Is the difference in average height of the samples large enough to be significant?

Here, the ranges of the two samples have a small overlap, so… We can analyse the spread of the heights of the students in the samples by drawing histograms 2 4 6 8 10 12 14 16 Frequency 140-149 150-159 160-169 170-179 180-189 Height (cm) C1 Sample D8 Sample Here, the ranges of the two samples have a small overlap, so… … the difference between the means of the two samples IS probably significant.

Here, the ranges of the two samples have a large overlap, so… 2 4 6 8 10 12 14 16 Frequency 140-149 150-159 160-169 170-179 180-189 Height (cm) C1 Sample Here, the ranges of the two samples have a large overlap, so… … the difference between the two samples may NOT be significant. 2 4 6 8 10 12 14 16 Frequency 140-149 150-159 160-169 170-179 180-189 Height (cm) D8 Sample The difference in means is possibly due to random sampling error

… and the spread of heights in each sample. To decide if there is a significant difference between two samples we must compare the mean height for each sample… … and the spread of heights in each sample. Statisticians calculate the standard deviation of a sample as a measure of the spread of a sample Sx = Σx2 - (Σx)2 n n - 1 Where: Sx is the standard deviation of sample Σ stands for ‘sum of’ x stands for the individual measurements in the sample n is the number of individuals in the sample You can calculate standard deviation using the formula:

It is much easier to use the statistics functions on a scientific calculator! e.g. for data 25, 34, 13 Set calculator on statistics mode MODE 2 (CASIO fx-85MS) Clear statistics memory SHIFT CLR 1 (Scl) = Enter data 2 5 DT (M+ Button) 3 4 1

Calculate the standard deviation Calculate the mean 24 AC SHIFT S-VAR (2 Button) 1 ( x ) = Calculate the standard deviation 10.5357 AC SHIFT S-VAR 3 = (xσn-1)

We start by calculating a number, t Student’s t-test The Student’s t-test compares the averages and standard deviations of two samples to see if there is a significant difference between them. We start by calculating a number, t t can be calculated using the equation: ( x1 – x2 ) (s1)2 n1 (s2)2 n2 + t = Where: x1 is the mean of sample 1 s1 is the standard deviation of sample 1 n1 is the number of individuals in sample 1 x2 is the mean of sample 2 s2 is the standard deviation of sample 2 n2 is the number of individuals in sample 2

Worked Example: Random samples were taken of pupils in C1 and D8 Their recorded heights are shown below… Students in C1 Students in D8 Student Height (cm) 145 149 152 153 154 148 157 161 162 158 160 166 163 167 172 175 177 182 183 185 187 Step 1: Work out the mean height for each sample C1: x1 = 161.60 D8: x2 = 168.27 Step 2: Work out the difference in means x2 – x1 = 168.27 – 161.60 = 6.67

Step 3: Work out the standard deviation for each sample C1: s1 = 10.86 D8: s2 = 11.74 Step 4: Calculate s2/n for each sample (s1)2 n1 = C1: 10.862 ÷ 15 = 7.86 (s2)2 n2 = D8: 11.742 ÷ 15 = 9.19

Step 5: Calculate (s1)2 n1 + (s2)2 n2 (s1)2 n1 + (s2)2 n2 = (7.86 + 9.19) = 4.13 Step 6: Calculate t (Step 2 divided by Step 5) t = (s1)2 n1 + (s2)2 n2 = x2 – x1 6.67 4.13 = 1.62

Step 7: Work out the number of degrees of freedom d.f. = n1 + n2 – 2 = 15 + 15 – 2 = 28 Step 8: Find the critical value of t for the relevant number of degrees of freedom Use the 95% (p=0.05) confidence limit Critical value = 2.048 Our calculated value of t is below the critical value for 28d.f., therefore, there is no significant difference between the height of students in samples from C1 and D8

Follow the instructions CAREFULLY Do not worry if you do not understand how or why the test works Follow the instructions CAREFULLY You will NOT need to remember how to do this for your exam