1. STC1204 Mid Term Public Speaking Preparation 5 questions Randomly Answer 1 question Date: 19 th April 2010 Monday Time: 4.15 – 6.00pm

2. Public Speaking Format 5 – 10 minutes Public Speaking per student Pick one of out 5 questions No preparation allowed Top 5 volunteer would get extra marks Reading would penalize marks Mark scheme: Content5 Grammar/Vocabulary2.5 Pronunciation2.5 TOTAL10

3. Question 1 1) Statistics is the science that deals with collection, tabulation and systematic classification of quantitative data. Discuss the two types of statistics. What is statistics? – Ordinary, straight forward concept – Make sense and be helpful in numerous situations – Powerful influence on our feelings, opinions and decisions that we make in life. – “the science that deals with collection, tabulation and systematic classification of quantitative data” – A way to take numbers and convert them into useful in formations so that good decisions can be made.

4. The field of Statistics can be categories into 2: - Descriptive Statistics → summaries/display data so that we can quickly obtain an overview - Inferential Statistics → make claims or conclusions about a population based on a sample of data Question 1

5. Descriptive Statistics - Being able to accurately summarize all data to get a look at the “big picture”, either graphically or numerically Question 1

6. Inferential Statistics - This category covers a large variety of techniques that make actual claims about population based on a sample of data Question 1

7. Descriptive vs. Inferential Statistics - The basic difference is that descriptive statistics reports on only the observations at hand and nothing more. Inferential statistics makes a statement about a population based solely on results from a sample taken from that population Question 1

8. Question 2 2) Data can be defined as the value assigned to a specific observation or measurement. Describe the types of data? What is data? – The basic foundation for field of statistics. – Defined as the value assigned to a specific observation or measurement. – Data is used to describe something interest about a population is called a “parameter”. – The data that is transformed into useful facts that can be used for a specific purpose (decision making) is called “information”. – One of the major reason to use statistics is to transform data into information.

9. Types of data is categories into 2 types: 1.Quantitative data 2.Qualitative data Question 2

10. Quantitative Data - Uses numerical values to describe something of interest. Qualitative Data -Uses descriptive terms to measure or classify something of interest. Question 2

11. Question 3 3) Nominal data is assigned to categories with no mathematical comparisons between observations. State your reason Levels of Measurement : 1.Nominal Level of Measurement 2.Ordinal Level of Measurement 3.Interval Level of Measurement 4.Ratio Level of Measurement

12. Nominal Level of Measurement - deals strictly with qualitative data. - stand alone and assigned to predetermined categories. - eg: types of insects, colors etc that will not allow performing mathematical operations. Question 3

13. Question 4 4) Describe in your own words the meaning of Measure of Dispersion Measures of Dispersion – Describe how far individual data values have strayed from the mean (average) – The ways to measure the dispersion of our data are range, variance (sample & population) and standard of deviation.

14. RANGE 1.The simplest measure of dispersion and is calculated by the difference between the highest value and the lowest value in the data set. 2.The range of a sample is obtained by subtracting the smallest measurement from the largest measurement 3.0 Measures of Dispersion

15. VARIANCE 1.One of the most common measurement of dispersion in statistics 2.Summarize the squared deviation of each data value from the mean. 3.The variance describes the relative distance between the data points in the sets and the mean of the set. 3.0 Measures of Dispersion

16. Variance (Group Data) σ² = ∑ n i =1 n σ² = the variance of the Group data X i = the values in the sample; X 1 = first data, X 2 = second data nn i =1 nm (x i - x ) fi x = the sample mean m = the number of classes (x i - x ) = the deviation from the mean for each value in the data set 2 fifi n = the total number of values in the data set 3.0 Measures of Dispersion

17. STANDARD DEVIATION 1.Very straightforward and clear 2.A standard deviation is the square root of variance. 3.Describe the actual and useful measure since the standard deviation is in the units of the original data sets Question 4

18. Std Deviation (Group Data) s = ∑ n i =1 n σ² = the variance of the Group data X i = the values in the sample; X 1 = first data, X 2 = second data nn i =1 nm (x i - x ) x = the sample mean m = the number of classes (x i - x ) = the deviation from the mean for each value in the data set 2 fifi f = the total number of values in the data set √ fi Question 4

19. Question 5 5) Most of our daily lives are surrounded by probability concept. Discuss the types of probability Terms widely used in probability: – Experiment → The process of measuring/observing an activity for the purpose of collecting data. Example: Rolling a pair of dice. – Outcome → A particular result of an experiment. Example: Rolling pair of dice with 3s with the dice – Sample Space → All possible outcomes of the experiment. Example: Sample space of rolling a pair of dice. {2,3,4,5,6,7,8,9,10,11,12} – Event → One or more outcomes that are of interest for the experiment and which is/are subset of the sample data. Example: Rolling a pair of a 2,3,4 or 5 with the 2 dice

20. CLASSICAL PROBABILITY 1.Refers to situation when we know the number of possible outcomes of the event of interest. 2.Can calculate the probability of that event with the following equation: P[A] = Number of possible outcomes in which Event A occurs Total number of possible outcomes in the sample space Question 5

21. EMPIRICAL PROBABILITY 1.Practice when don’t know enough about the underlying process to determine the number of outcomes associated with the event 2.Requires that you count the frequency that an event occurs through an experiment and calculate the probability from the relative frequency distribution. P[A] = Frequency in which Event A occurs Total number of observations Question 5

22. SUBJECTIVE PROBABILITY 1.Is used when classical and empirical probabilities are not available. 2.Under these circumstances, we rely on expertise, experience and instinct to estimate the probabilities Question 5