Scientific Lab Report Pre-AP

Problem:

  • The problem must be written in a question format that can be answered through a controlled experiment. (What are you trying to find out?) Forexample: Will fertilizer make plants grow taller?

Hypothesis:

  • This is an educated guess, based on previous research or prior knowledge.
  • If (the independent variable) is (action), then (the dependent variable) will (result) because (why). Example: If different amounts of fertilizer are applied to plants (independent variable + action), then plants with the most fertilizer (dependent variable) will grow the most (action) because the fertilizer will provide important nutrients to the growing plant (logical reason why).

Materials:

  • Material should be a bulleted or numbered list of allitems used in the experiment
  • Include metric sizes and amounts, as well as how many of each item needed.

Example:

  1. 9 identical seedlings
/ 4. 270 mL liquid fertilizer / 7. 4.5 L soil
  1. 9 identical pots
/ 5. Three 250mL beakers / 8. Tape and marker for labeling
  1. Tap water
/ 6. 10mL graduated cylinder / 9. Meter stick

Procedure:

  • The procedure is a set of numbered step-by-step instructions telling exactly what to do. This is very specific and detailed. Do not assume the reader has prior knowledge.
  • Do not include pronouns (I, we, he, she, they, them, you, our, us, it, etc.) – they are not specific or clear
  • Must demonstrate an understanding of scientific experimental thought and must be measureable.
  • Repeated trials are required. This means that the procedure must be repeated at least 3 times and the data averaged. Repeated trials help to minimize error and make data more accurate.

D
R
Y
M / I / X
  • Identify the independent (manipulated) variable.
  • What YOU are testing
  • What YOU change (the cause)
  • Example: The different amounts of fertilizer applied to 3 different plants.
  • Written on the horizontal or x-axis of a graph (hint: MIX – Independent on the X)
  • Usually the first column in a data table with metric units
  • Identify the dependent (responding) variable.
  • What reacts or responds to your changes (the effect)
  • What you measure in the experiment
  • Example: Plants with no fertilizer grew 10 cm, while plants with 10mL fertilizer grew 20 cm and plants with 20mL fertilizer grew 40 cm.
  • Written on the vertical or y-axis of a graph (hint: DRY – Dependent on the Y)
  • Identify the constants. These are all the details that must stay the same during the experiment. For example: same type and size of pot, same type and amount of soil, same type and amount of water, same type of original size of plant, same amount and intensity of sunlight, temperature
  • Identify the control (or control group). This is the part of the experiment that you don’t change (example: water only with no fertilizer). You compare the control to the other parts of the experiment that were tested (example: water with fertilizer). This is the only way you can see if there was any change due to the variable tested. Be sure to include any warnings necessary for lab safety.
  • Example:
  1. Carefully remove each seedling from original pot.
  2. Open bag of soil.
  3. Place each seedling in a separate pot with 500mL of soil, ensuring that the roots are well covered and the leaves are above the soil level.
  4. Mark each pot Trial 1 A, Trial 1 B or Trial 1 C and place in a sunny spot. Measure and record the initial height of each plant.
  5. Mark each of the 3 beakers as A, B, or C.
  6. Place 50 mL of water into beaker A. Add to pot A.
  7. Place 50 mL of water into beaker B. Using gloves, safety glasses and a graduated cylinder, carefully measure 10 mL of liquid fertilizer. Gently add the fertilizer to the water, avoiding splashing. Stir gently until mixed and then add to pot B.
  8. Place 50 mL of water into beaker C. Using gloves, safety glasses and a graduated cylinder, carefully measure 20 mL of liquid fertilizer. Gently add the fertilizer to the water, avoiding splashing. Stir gently until mixed and then add to pot C.
  9. Repeat steps 1-9 two more times with new plants and materials. Be sure to change the labels for each set to read trial 2 or trial 3 and to place all 9 pots in the same environment.
  10. On the next day, do nothing.
  11. On the second day, repeat steps 6-8 for all 9 plants. Continue watering every other day for 14 days. After 14 days of growth, measure and record the growth of each plant.

Data/Results:

  • Create a data table. Be sure to include title, labels and metric units. Independent variable should be in the first column and dependent variable should be in the right column(s). Example:

Plant Growth with Different Amounts of Fertilizer

Fertilizer Added / Trial 1 Growth (cm) / Trial 2 Growth (cm) / Trial 3 Growth (cm) / Average Growth (cm)
50 mL water only / 11 / 9 / 10 / 10
50 mL water and 10 mL fertilizer / 19 / 20 / 21 / 20
50 mL water and 20mL fertilizer / 41 / 40 / 39 / 40
  • Create a graph from the data table. Be sure to create the most appropriate type of graph and include all graph ingredients. The graph should be drawn by computer or with pencil and ruler on graph paper to ensure straight lines. Remember to mark the origin (the intersection of the x and y axis) with a zero. Label the x-axis with the independent variable (and units used) and the y-axis with the dependent variable (and units used). Both the x and y-axis should be divided into reasonable, evenly spaced intervals that match the data. Each line must represent the same amount of change. Include a descriptive title that includes the independent and dependent variables. Remember thatcircle (or pie) graphs are used to show how a share or part of something relates to the whole and is often written as a percent, such as the percentage of males and females driving big rig trucks. Bar graphs are used to compare amounts, quantities and change, such as populations in different states. Line graphs are used to show patterns and trends over time, comparing two sets of numbers and to help you see changes over time, such as plant growth over a week’s time.
  • Remember that graphs and data tables are used to make data easier to read and understand. They allow data to be visualized in a scientific manner, to aid in analyzing information and to predict outcomes.
  • Example:

Data Analysis:

  • Explain charts, data tables and graphs. This should be incomplete sentences and tell patterns or trends. Explain what the data shows.
  • Include quantitative data (quantities, measurements or numbers, such as 12 cm) as well as qualitative data (its qualities, descriptive observations of what it is like, such as color, shape, health etc.)
  • Example: The data shows that as fertilizer amounts were increased, plant growth increased as well. With water only, the control group grew an average of only 10 cm. Group B, with 10 mL liquid fertilizer mixed into the water grew an average of 20 cm, double the growth of the control group. The leaves were a dark green color and the plants stood straight. Group C, with 20 mL liquid fertilizer grew an average of 40 cm, four times the growth of the control group. By the end of the 14 days, however, the leaves were turning yellow and were wilted. They had to be held up to measure accurately.

Conclusion:

  • The hypothesis is (choose accepted or rejected). The hypotheses stated “word for word repeat the hypothesis”. To test the hypothesis (summarize the procedure in a sentence or two, making sure to mention tools used). During the experiment it was observed (list observations, including at least one quantitative and one qualitative observation that support or refute your hypothesis. Also include any errors that may have affected the results). Therefore, (if the hypothesis was accepted, simply repeat it again here. If it was rejected, state a better hypothesis for further study).
  • Example: The hypothesis is accepted. The hypothesis stated “If different amounts of fertilizer are applied to plants, then plants with the most fertilizer will grow the most because the fertilizer will provide important nutrients to the growing plant.” To test the hypothesis, plants were divided into 3 groups. The control group received 50 mL of water only. Group B received 10 ml of liquid fertilizer mixed into the water and group C received 20 mL of liquid fertilizer in addition to the water. All plants were watered every other day and total growth was measured after 14 days. During the experiment it was observed that Group C, the plants that received the 20 mL of fertilizer grew an average of 30 cm taller than the control group without fertilizer. It was also observed that group Bgrew taller than the control group. Therefore, if fertilizer is applied to plants, then the plants with the most fertilizer added will have the greatest growth.
  • Example of a rejected hypothesis: The hypothesis is rejected. The hypothesis stated “If different amounts of fertilizer are applied to plants, then plants with the most fertilizer will grow the most because the fertilizer will provide important nutrients to the growing plant.” To test the hypothesis, plants were divided into 3 groups. The control group received 50 mL of water only. Group B received 10 ml of liquid fertilizer mixed into the water and group C received 20 mL of liquid fertilizer in addition to the water. All plants were watered every other day and total growth was measured after 14 days. During the experiment it was observed that the plants that received the 20 mL of fertilizer grew an average of 30 cm taller than the control group without fertilizer and 20 cm taller than the group with only 10 mL of fertilizer added. However, it was also observed that group C had leaves that were yellowing and wilting, and though this group grew the most, the plants were nearly dead and had to be held up to measure. Therefore, a better hypothesis would be “If different amounts of fertilizer are applied to plants, then the plants with 10 mL fertilizer added will have the healthiest growth pattern.”
  • The hypothesis from the beginning of this experiment left out some details and the data showed the error made. A hypothesis should be testable, but specific. A hypothesis that is not specific enough, such as not mentioning the overall health of the plant in the above example, often yields data than can be manipulated to prove or reject the hypothesis depending on how the data is interpreted. However, errors like this are often the place to start when designing the next experiment. For example, the researcher may next try the same experiment, but only adding fertilizer every 10 days and just water all the other days to see if the data is more supportive of the hypothesis. Or, they may change the amount of water in each trial to dilute the fertilizer more, or maybe cut back on the amount of fertilizer. Many new experiments can be designed by analyzing little observations during the experiment. This is why it is important to make frequent logs of all observations and measurements, even if you don’t think they are relevant to the hypothesis. Just remember that the observations included in the conclusion should directly support or refute your hypothesis.