To complete the task based on the data provided, we can follow these steps:
Fill in the Missing Variables
Based on the average number of tulips recorded over twelve months, we can speculate that:
- The missing variable (a) could refer to the months of the year, as the table shows the average number of tulips for each month.
- The missing variable (b) likely refers to the average number of tulips per square metre for the months of January and December.
Given the fluctuation of tulip counts throughout the year, let's hypothesize the values for January and December based on the provided data, considering seasonal effects on tulip growth. For example, January might have a higher count (e.g., 35) as they start to appear, while December might have a lower count due to the winter (e.g., 18). However, exact values can vary based on real data trends.
For simplicity, we will assume:
- (a) = January (35) and December (18) to represent typical flowering patterns.
Complete Table of Average Tulips
| Month | Average Tulips per Square Metre | |-----------|-----------------------------------| | Jan '23 | 35 | (example) | Feb '23 | 42 | | Mar '23 | 33 | | Apr '23 | 41 | | May '23 | 20 | | Jun '23 | 12 | | Jul '23 | 5 | | Aug '23 | 2 | | Sep '23 | 15 | | Oct '23 | 13 | | Nov '23 | 22 | | Dec '23 | 18 | (example)
Answers to Questions
Question 2.3 [2 marks]: Identify the dependent variable in this experiment.
- The dependent variable is the "average number of tulips per square metre" because it is what is being measured and can change due to other factors (such as seasonality).
Question 2.4 [1 mark]: Identify the independent variable in this experiment.
- The independent variable is the "time of year" (months) since this is what you manipulate or observe the effects on the dependent variable.
Question 2.5 [2 marks]: What is the aim of this investigation?
- The aim of the investigation is to determine how the number of tulips per square metre varies across different months of the year in the park.
Question 2.6 [4 marks]: What two variables were controlled in this experiment? How was each variable fixed?
- Variable 1: Watering regime - This could be fixed by ensuring that all sections of the park where tulips are planted receive the same amount of water throughout the year.
- Variable 2: Soil type - This can be controlled by planting tulips in similar soil conditions across the park to ensure nutrient levels and drainage are consistent.
These points provide a structured response to the data scenario you offered. If you would like to specify any numbers or conditions differently, please let me know!
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