Read a biology experiment: variables, controls, repeated trials

Grade 9 Science Worksheet - Building Confidence

Circle the best answer.

1. Read this first

   Yeast test of a new sweetener (example data)

   bottle	added to the yeast and water	gas in 10 minutes (mL)
   1	nothing	2
   2	new sweetener	3
   3	glucose	21

2. 1.

   Ari tests whether yeast can use a new sweetener. Which bottle is the negative control?

   • Bottle 2: the sweetener, since it is the thing being tested
   • Bottle 1: nothing is added, so it shows the background gas
   • No bottle, since the three have yeast in them
   • Bottle 3: glucose, since yeast is known to respond to it
3. 2.

   Bo reads the same results. Which bottle is the positive control, and what does it show?

   • Bottle 3: glucose feeds yeast, so it shows the setup can detect gas
   • Bottle 2: it has the sweetener that the test is about
   • Bottle 1: it shows the setup gives no gas without sugar
   • Neither control matters; the sweetener bottle answers the question by itself

4. The same test on another day (example data)

   bottle	added to the yeast and water	gas in 10 minutes (mL)
   1	nothing	2
   2	new sweetener	3
   3	glucose	2

5. 3.

   Esme gets these results on another day. What should Esme conclude about the sweetener?

   • The sweetener does not work, since bottle 2 made little gas
   • Nothing yet: the glucose bottle made no gas, so the test itself failed
   • Yeast cannot use any sugar, so the sweetener fails too
   • The sweetener works as well as glucose does

6. Gas from yeast (example data)

   time (min)	gas (mL)
   0	0
   4	12
   10	36

7. 4.

   Kira reads the gas table. What is the mean rate of gas production between minute 4 and minute 10?

   • 3.6 mL per minute
   • 24 mL per minute
   • 4 mL per minute
   • 6 mL per minute

8. Gas from three yeast batches (mL in 10 minutes) (example data)

   batch	trial 1	trial 2	trial 3
   A	14	15	16
   B	10	15	20
   C	13	15	17

9. 5.

   All three batches have a mean of 15 mL. Milo asks which batch's trials agree best.

   • Batch C, because its range is the middle one
   • Batch B, because its trials cover the most values
   • Batch A, with the smallest range, 2 mL
   • The three agree equally, because their means match

10. One seedling (example data)

    day	height (cm)
    3	2
    9	14

11. 6.

    Noah measures one seedling twice. What is its mean growth rate between day 3 and day 9?

    • 4.7 cm per day
    • 12 cm per day
    • 1.6 cm per day
    • 2 cm per day

12. Batch A, four trials (mL in 10 minutes) (example data)

    trial	gas (mL)
    1	14
    2	15
    3	16
    4	31

13. 7.

    One bottle in batch A was shaken before it was read. Pia wants a summary of a typical trial. Which summary is best?

    • The mean, 19 mL, since it uses each trial
    • The largest trial, 31 mL, since it shows what the yeast can do
    • The median, 15.5 mL, which the extreme trial does not pull up
    • The range, 17 mL, since it uses the extreme trials

14. Gas from yeast in 10 minutes, mean of 3 bottles (example data)

    water temperature (°C)	mean gas (mL)
    20	8
    30	15
    40	22

15. 8.

    Ren writes: "At 50 °C the yeast will make about 29 mL." What is the best reply?

    • Supported: the pattern adds 7 mL for each 10 °C
    • Supported: warmer water gives more gas at any temperature
    • Not supported: the means are too small to compare
    • Not supported: 50 °C was not tested, and heat can slow yeast

16. Bean seeds sprouted of 50 per dish (example data)

    salt (g per L)	seeds sprouted
    0	46
    4	21

17. 9.

    Tala tested bean seeds only. A poster says salt lowers sprouting in all seeds. What is the best reply?

    • Not supported: 50 seeds per dish is too few for beans
    • Supported: beans are seeds, so all seeds must behave alike
    • Supported for beans only; other seeds were not tested
    • Supported: 25 fewer seeds sprouted, which is enough for each kind
18. 10.

    Example data. Bubbles counted by eye in one bottle: 38, 41, 40, 43 in four trials of equal length. Zee counts bubbles by eye, so the counts differ from trial to trial. What does averaging more trials do?

    • It removes the chance errors, because each count becomes the same
    • It shrinks the chance errors, because high and low counts balance out
    • It adds more chance errors, because more trials add more counts
    • It changes nothing, because each count is already right