1. How to Write a Descriptive Methods Section

2. Step 1
Organize the steps into small, discrete directions in the order you would do them in the lab.
Good
Bad
1. Wake up.
1. Get up.
2. Put your feet on the floor.
2. Get out of bed.
3. Stand up.

3. Step 2 Avoid using pronouns Good: “Place the beaker on the table.”
Bad: “Place it on the table.”

4. Step 3 Use commands Good: “Measure 50 mL of water.”
Bad: “50 mL of water.”

5. Step 4 Eliminate extra information Good: “Measure 50 mL of water.”
Bad: “Measure 50 mL of good, clean, fresh, great-tastin’ water!”

6. Step 5
If applicable, sketch and label the experimental set-up. It does NOT have to cover each step.

7. Step 6
Include all step. No matter how small the step seems, it may be the critical step for a researcher to replicate the procedure.
Ex:
Place the beaker on the hot plate.
Record the change in water temperature every 5 minutes.

8. Practice Research Topic: Popcorn
Use the Four Question Strategy to design an experiment.

9. Analyzing Experimental Data

10. Types of Data
Quantitative Data: represented by a number and a unit of measurement that is based upon a standard scale with equal intervals, such as the Metric system
Ex: height of a person in meters, mass of a rabbit in kilograms
Continuous data: collected using standard measurement scales that are divisible into partial units
Ex: distance in kilometers, volume in liters
Discrete data: collected using standard scales in which only whole integers are used
Ex: number of wolves born in a given year, number of people that can touch their toes

11. Types of Data Quantitative
Ratio Data: quantitative data are collected using a standard scale with equal divisible intervals and an absolute zero
Ex: temperature of a gas on the Kelvin scale, velocity of an object in m/sec, distance from a point in meters
Interval Data: the scales does not have an absolute zero
Ex: temperature of a substance on the Celsius scale

12. Types of Data Qualitative Data: categorized into 2 categories
Discrete: represented by a word or “number” label or measurements made with a nonstandard scale with unequal intervals; reflect a synthesis of many observations made during experimentation
Nominal data: exists when objects have been named or placed into discrete categories that cannot be rank ordered
Ex: gender, color of hair
Ordinal data: exists when objects are placed into categories that can be rank ordered
Ex: activity of an animal on a scale of 1 – 5.

13. Heights of Plants Health of Plants Leaf Quality
Practice
Classify the three dependent variables in Mary’s experiment as quantitative or qualitative data
Heights of Plants Health of Plants Leaf Quality

14. Heights of Plants Health of Plants Leaf Quality
Practice
Classify the three dependent variables in Mary’s experiment as quantitative or qualitative data
Heights of Plants Health of Plants Leaf Quality
Quantitative (continuous) Qualitative Qualitative
Ratio (equal intervals, ab. 0) Nominal (discrete cats., Ordinal (discrete cats., ranked)
not ranked)

15. Describing Data
Measure of central tendency: the one number that is most typical of the entire set of data
Mode: the value of the variable that occurs most often; used for data at the nominal, ordinal, interval, or ratio levels
Median: the middle value, after all of the cases have been rank ordered from highest to lowest; can be used with ordinal, interval, or ratio data
Mean: the arithmetic average or the sum of the individual values divided by the number of cases; can only be calculated for interval or ratio data

16. Describing Data Variation: spread within the data
Range: computed by finding the difference between the smallest (minimum) and the largest (maximum) measure of the dependent variable
Ex: plant height
Frequency distribution: depicts the number of cases falling into each category of the variable
Ex: the color of tomatoes produced with different fertilizers

17. Height of Plants Health of Plants Leaf Quality
Practice
Determine the most appropriate measures of central tendency and variation to calculate for each of the dependent variables in Mary’s experiment:
Height of Plants Health of Plants Leaf Quality

18. Height of Plants Health of Plants Leaf Quality
Practice
Determine the most appropriate measures of central tendency and variation to calculate for each of the dependent variables in Mary’s experiment:
Height of Plants Health of Plants Leaf Quality
Mean, Range Mode, Freq. Dist. Median, Freq. Dist.