1.3 Evaluating Results

• Reliability ensures results are consistent when the experiment is repeated.


  True
• What is an example of an exponential trend?

  Population doubles every 10 years
• Order the types of data trends from slowest to fastest rate of change:

  1️⃣ Linear Trend

  2️⃣ Exponential Trend

  3️⃣ Periodic Trend
• Environmental factors like temperature can affect experimental results.


  True
• A p-value of 0.02 means there is a 2% chance results are random
• An exponential trend in data analysis describes data that increases or decreases rapidly
• Measurement errors occur due to inaccuracies or imprecision in measuring instruments
• What does a p-value of less than 0.05 suggest in statistical significance?

  Statistically significant results
• Steps to develop conclusions supported by data:

  1️⃣ Summarize findings

  2️⃣ Interpret the data

  3️⃣ Connect to the hypothesis

  4️⃣ Highlight limitations
• The independent variable is the factor you manipulate
• ANOVA is used to compare the means of three or more groups
• What does accuracy measure in experimental results?

  Closeness to true value
• What does validity ensure in an experiment?

  Measures what it should
• What is a common source of experimental error related to instruments?

  Measurement errors
• Match the aspect with its definition:

  Statistical Significance ↔️ Results due to variables, not chance

  p-value ↔️ Probability results are random
• When examining data from an experiment, it is important to look for data trends and patterns
• What is a periodic trend in data analysis?

  Data fluctuates in regular intervals
• What is an example of an environmental factor that can affect experimental results?

  Temperature
• Match the scenario with its interpretation and conclusion:

  Fertilizer Growth with p-value 0.03 ↔️ Statistically significant effect of fertilizer on plant growth

  Temperature and Enzyme Activity with p-value 0.10 ↔️ No statistically significant effect of temperature on enzyme activity
• What is a well-supported conclusion based on data from a plant growth experiment?

  The plant treated with Fertilizer A grew 50% taller than the control
• What is the final step in formulating and testing a hypothesis?

  Draw conclusions
• Precision refers to how close repeated measurements are to each other
• A linear data trend occurs when data increases or decreases at a constant
• A periodic trend in data fluctuates in regular intervals.


  True
• Experimental design flaws can introduce bias
• What p-value suggests statistical significance?

  $p < 0.05$
• What is a linear trend in data analysis?

  Data increases at a constant rate
• Identifying data trends is crucial for understanding the underlying relationships in an experiment


  True
• Accounting for sources of error and uncertainty enhances the reliability of experimental findings

  True
• Statistical significance should be evaluated in conjunction with the experiment's accuracy, precision, reliability, and validity
• A well-supported conclusion must reference specific data and acknowledge limitations


  True
• Analyzing data is necessary to determine whether a hypothesis is supported or rejected


  True