hypothesis testing, confidence intervals and power of study

Question 1

Statistics

Answer 1

a way to get information from data

Question 2

Why we study statistics

Answer 2

• The need to read and interpret the published research of other
• Epidemiology is becoming more quantitative
• Consider how reliable a diagnostic test is
• To understand safety and efficacy of a new drug assessed
• To understand how safety and quality of food for human consumption is assessed

Question 3

What statistics involves?

Answer 3

• Designing experiments/ a survey/ fieldwork
• Collection of data
• Analysis of data
• Summarising information to aid understanding
• Interpretation of the analyses and drawing conclusions from data

Question 4

Components of research questions

Answer 4

• Domain or study sample
• Exposure/ determinant
• Outcome

Question 5

Data

Answer 5

information, such as facts or numbers, collected together to be examined

Question 6

Variables

Answer 6

an element, feature, or factor that is liable to vary or change. For example: each leaf has some attributes (biological surfaces of the leaf, length, colour, surface area etc) that changes among the leaves

Question 7

describe the classification of variables

Answer 7

• Categorical or qualitative, divided into nominal and ordinal
• Numerical or quantitative, divided into discrete and continuous

Question 8

Categorical or qualitative variables

Answer 8

describe a characteristic that can’t easily be measured but can be observed subjectively

Question 9

Ordinal variables

Answer 9

characteristics with clear ordering

Question 9

Nominal variables

Answer 9

characteristics with no ordering of the categories (binary variable)

Question 10

Numerical or quantitative variables

Answer 10

describe a measurable quantity on a well-defined scale

Question 11

Discrete variables

Answer 11

data that can take only integer values

Question 12

Continuous variables

Answer 12

the data can have almost any numeric value and can be divided into finer and finer levels

Question 13

Descriptive statistics (or summary statistics)

Answer 13

summarising your data by using tables, diagrams, summary measures (e.g. mean and standard deviation), identifying the underlying frequency distribution (e.g. data obey a normal distribution)

Question 14

Inferential statistics

Answer 14

based on data from a sample you are trying to reach conclusions that apply to the entire population

Question 15

Inferential statistics includes

Answer 15

• population
• Sample
• Focus on your sample and measure/ estimate what you are interested in
• Confidence intervals
• Hypothesis testing

Question 16

Sample

Answer 16

• every element from the population has the same probability to be in the sample
• Infer conclusions from this samples for the entire population

Question 17

Confidence intervals

Answer 17

an estimated interval within which an unknown parameter may plausibly lie

Question 18

The function of confidence intervals

Answer 18

Give you an idea of where the true value of what you are measuring lies and p-value summarise the strength of the evidence against the null hypothesis

Question 19

Calculating confidence intervals

Answer 19

• Dependant on what you are measuring under the general assumptions
• Estimation

Question 20

hypothesis

Answer 20

an educated guess about something in the world around you based on facts but has not yet been proved

Question 21

hypothesis testing

Answer 21

formal procedures to accept or reject statistical hypotheses

Question 21

null hypothesis

Answer 21

usually denoted by H0….

Question 22

alternative hypothesis

Answer 22

the alternative hypothesis, denoted by H1, is contrary to the null hypothesis

Question 23

what us the hypotheses texting usual procedure

Answer 23

• formulate the null and alternative hypotheses
• collect the data and look at them, look for outliers
• formulate an analysis plan
• identify a correct test statistics
• calculate p-value
• interpret and make a decision

Question 24

p-value