1. Quantitative Analysis: Basics Sebastian M. Rasinger Quantitative Research in Linguistics. An Introduction 2 nd edition. 2013. London: Bloomsbury S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

2. Agenda Statistics – what for? Quantitative data – what, how, why? Descriptive statistics –frequencies –Measures of location –Measures of dispersion Relationships between variables S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

3. What is statistics? Any orderly summary of numbers, e.g. results of an election, league table etc Numerical measurement describing some characteristic of a sample Collection of methodological tools which help to systematically and exemplarily collect, process and display information, e.g. inflation rate, unemployment rate S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

4. Statistics as a basis for decisions Numerous possibilities to process an issue statistically  problem of measurement Different interpretation of results: glass half empty or half full? Manipulation of raw data S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

5. Statistics: 3 purposes Description: –Quantifying and summarising information in order to describe and display an issue in the most effective and optimal manner: tables, graphs, main statistical values –Aim: describing the reality S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

6. Statistics: 3 purposes (cont’d) Generalisation: –Inference: inferring information about the population via a small sample Population sample S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

7. Statistics: 3 purposes (cont’d) Identification of causal relationships, i.e. how two (or more) phenomena are related e.g. effect of learner’s age on language attainment S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

8. Quant. Data: discrete or continuous Discrete: finite or countable number of possible values –E.g. numbers of students in a class (there’re no half students…) Continuous: infinitely many possible values on a continuous scale without gaps/interruptions –E.g. amount of coffee a university lecturer drinks a day: continuous (e.g. 1.256 litres) S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

9. Levels of measurement Nominal data: –names, labels, categories. Cannot be arranged in high/low scheme, e.g. sex Ordinal data: –Data may be arranged in some order, but differences between value cannot be determined or are meaningless, –e.g. ‘good’ – ‘average’ – ‘poor’ rankings S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

10. Levels of measurement (2) Interval data: –meaningful difference between data, but no natural zero starting point for when no quantity is present, e.g. Fahrenheit: 0° doesn’t mean no heat Ratio data: –Natural zero point, e.g. length of lecture in minutes: 0 minutes = no lecture S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

11. Absolute and Relative frequency Students on a year 1 UG course achieved the following results in an exam 1st class4 Upper Second Class8 Lower Second Class11 Third Class3 Fail1 Absolute frequency S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

12. Absolute & Relative frequency (2) Relative frequency: Where n is the total number of items/observations in a sample S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

13. Relative frequency Abs.Rel.% 1st class40.148114.81 Upper Second Class80.296329.63 Lower Second Class110.407440.74 Third Class30.111111.11 fail10.0373.7 271100 Percentage: relative frequency x 100 S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

14. Summarizing data: classes and class width The following table shows the number of students for 20 courses over the last year  No obvious classes. Useless information. 1.Determine number of non-overlapping classes 2.Determine the width of each class 3.Determine the class limits 1214191815 18172027 22232221332814181613 S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

15. Classes and class width 1.20 observations  5 classes reasonable 2.Width of classes 3.Class limits Lower limit: smallest possible value in a class Upper limit: largest possible value in a class Number of classes, width and limits depend on researcher’s judgement S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

16. Classes and class width (cont’d) Class intervalsFrequencyRelative frequency 10-1440.20 15-1980.40 20-2450.25 25-2920.10 30-3410.05 Total201 S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.

17. Cumulative frequencies Running total of frequencies through all classes Class intervalsfRf cfcRf 10-1440.2040.20 15-1980.40120.60 20-2450.25170.85 25-2920.10190.95 30-3410.05201 Total201 S.M.Rasinger. 2013. Quantitative Research in Linguistics. 2e. Bloomsbury.