Clinical stats 2

Question 1

❓ What is a normal distribution?

Answer 1

📈 A bell-shaped, symmetrical curve where mean = median = mode.

Question 2

What are some examples of normally distributed variables?

Answer 2

📏 Height
⚖️ Weight
🎓 IQ
🦴 Bone density
🧪 Blood pressure
📝 Exam scores

Question 3

What happens when the standard deviation is small?

Answer 3

📉 The curve is narrow and peaked – values are close to the mean.

Question 4

What does a large standard deviation mean?

Answer 4

📉 The curve is wider – data is more spread out.

Question 5

What two parameters determine the shape of a normal curve?

Answer 5

1️⃣ Mean (μ): centre of the curve
2️⃣ Standard deviation (σ): how spread out the data is

Question 6

What % of data lies within 1 SD from the mean?

Answer 6

➗ 68%

Question 7

What % of data lies within 2 SDs from the mean?

Answer 7

🧮 95%

Question 8

What % of data lies within 3 SDs from the mean?

Answer 8

📏 99.7%

Question 9

Should you check for normality even if the variable (e.g. height) is usually normal?

Answer 9

✅ Yes! Because samples may differ from the population.

Question 10

Why is checking for normality important?

Answer 10

📊 Many statistical tests (t-tests, ANOVA, regression) assume the data is normally distributed.

Question 11

What is the difference between population and sample?

Answer 11

👥 Population: all individuals/items of interest
🧪 Sample: a subset drawn from the population

Question 12

❓ What do descriptive statistics do?

Answer 12

📋 They describe the sample only.

Question 13

What do inferential statistics do?

Answer 13

🔮 They help us make predictions or conclusions about the population from the sample.

Question 14

❓ Give an example of a population parameter vs. sample statistic:

Answer 14

📌 Population: average times kids brush teeth daily
📌 Sample: brushing frequency in 50 kids

Question 15

What is sampling variation?

Answer 15

🎲 Random differences in statistics from sample to sample.

Question 16

What is standard error (SE)?

Answer 16

📉 A measure of how much a sample mean varies from the true population mean.
👨‍👩‍👧‍👦 Larger samples → smaller SE.

Question 17

What is the formula for a 95% confidence interval?

Answer 17

🧮 CI = 1.96 × SE

Question 18

What does a 95% confidence interval mean?

Answer 18

🎯 There is a 95% chance the true population mean lies within the calculated range.

Question 19

Example interpretation: CI = (29.57, 46.91)?

Answer 19

✅ We are 95% confident that the true population mean lies between 29.57 and 46.91.

Question 20

what is sample

Answer 20

set of data drawn form the population

Question 21

what is population

Answer 21

group of all items of interest

Question 23

what is descriptive statistics

Answer 23

• desicbre the data set but doesn’t allow us to draw any conclusion or make any interferences about the data

Question 24

What is inferential statistics

Answer 24

• draw conclusion or inferences about characteristics of populations based on data forma. sample

Question 25

what is statistical inferece-

Answer 25

process of making an estimate, prediction or decision about a population based on a sample

Question 26

Which of the following about the normal distribution is NOT true? Theoretically, the mean, median, and mode are the same. About 2/3 of the observations fall within 1 standard deviation from the mean. It is a discrete probability distribution. It is symmetrical

Answer 26

C- it is a discrete probability disitbution

Question 27

What is sampling variation?

Answer 27

Statistics vary from sample to sample due to random chance. Example: A population of 100,000 people has an average IQ of 100 (If you actually could measure them all!) If you sample 5 random people from this population, what will you get?

Question 28

What is standard Error

Answer 28

a measure of sampling variability.

Question 29

with affect does increase sample size have on standard error

Answer 29

Standard error decreases with increasing sample size N and increases with increasing variability of the outcome (SD σ).

Question 30

A 95% confidence interval for a mean: a- Is wider than a 99% confidence interval. b- Is wider when the sample size is larger. c-In repeated samples will include the population mean 95% of the time. d- Will include 95% of the observations of a sample.

Answer 30

c

Question 31

Suppose we take a random sample of 100 people. We form a 90% confidence interval of the true mean population height. Would we expect that confidence interval to be wider or narrower than if we had done everything the same except sampled 200 people? A- Narrower B- Wider C- Exactly the same D- It is impossible to predict

Answer 31

A N increases so stnadard Error decreases

Question 32

How do we addrsss categoric data

Answer 32

proportion. of aprituclar outcome is p -

Question 33

What is the sampling disitubtion of P

Answer 33