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.

   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

3. 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

4. 2.

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

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

5. Bean seedlings after 14 days (example data)

   group	mean height (cm)
   without plant food	12
   with plant food	15

6. 3.

   Jun compares the two groups. By what percent are the fed seedlings taller than the unfed ones?

   • 125 percent
   • 20 percent
   • 25 percent
   • 3 percent

7. Gas from yeast (example data)

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

8. 4.

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

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

9. Seeds sprouted after 7 days, 20 seeds per dish (example data)

   dish	seeds sprouted
   control	12
   treated	17

10. 5.

    In the treated dish, Luz counts how many seeds sprouted. By how many percentage points is sprouting higher than in the control?

    • 5 percentage points
    • 42 percentage points
    • 25 percentage points
    • 85 percentage points

11. 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

12. 6.

    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
    • The three agree equally, because their means match
    • Batch A, with the smallest range, 2 mL

13. One seedling (example data)

    day	height (cm)
    3	2
    9	14

14. 7.

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

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

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

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

16. 8.

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

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

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

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

18. 9.

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

    • Supported: beans are seeds, so all seeds must behave alike
    • Not supported: 50 seeds per dish is too few for beans
    • Supported for beans only; other seeds were not tested
    • Supported: 25 fewer seeds sprouted, which is enough for each kind
19. 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 adds more chance errors, because more trials add more counts
    • It changes nothing, because each count is already right
    • It shrinks the chance errors, because high and low counts balance out