σN Fg (Newton) σf Weight (Newton 29.3o 1.777   0.8544   1.963 Fill out rest of table. The table is that of slope forces. N = Normal Force got from equation N = m × Az Az = acceleration in z direction Az = (8.795 ± 0.022) m/s2 m = mass  m = (0.2016 kg ± 0.00584 kg) Fg = Force exerted by gravity got from equation Fg = m×|Ay| Ay = acceleration in y direction  Ay = (-4.253 ± 0.015) m/s2 m = mass  m = (0.2016 kg ± 0.00584 kg) The photo is the equation needed to be used to fill in the rest of the table.

College Physics
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Chapter1: Units, Trigonometry. And Vectors
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Angel N (Newton) σN Fg (Newton) σf Weight (Newton
29.3o 1.777   0.8544   1.963

Fill out rest of table. The table is that of slope forces.

N = Normal Force

  • got from equation N = m × Az
    • Az = acceleration in z direction
      • Az = (8.795 ± 0.022) m/s2
    • m = mass 
      • m = (0.2016 kg ± 0.00584 kg)

Fg = Force exerted by gravity

  • got from equation Fg = m×|Ay|
    • Ay = acceleration in y direction 
      • A= (-4.253 ± 0.015) m/s2
    • m = mass 
      • m = (0.2016 kg ± 0.00584 kg)

The photo is the equation needed to be used to fill in the rest of the table.

## Data Analysis of Accelerometer and Force Measurements

### Accelerometer Graph

The accelerometer readings are depicted in the first graph. It shows accelerations in three axes, but currently, the Ay (blue) and Az (green) axes are selected. The x-axis represents time (in seconds), and the y-axis shows acceleration (in m/s²).

- **Selected Axes:**
  - Ay (blue line)
  - Az (green line)

- **Key Statistics:**
  - Time Interval (Δt): 10.73500 seconds
  - **Ay:**
    - Mean (μ): -4.253 m/s²
    - Standard Deviation (σ): 0.015 m/s²
    - Acceleration (a): -45.654 m/s
    - Slope (s): 0.00 m/s³ (r²: 0.01)
  - **Az:**
    - Mean (μ): 8.795 m/s²
    - Standard Deviation (σ): 0.022 m/s²
    - Acceleration (a): 94.410 m/s
    - Slope (s): -0.00 m/s³ (r²: 0.00)

### Force Graph

The second graph represents the force applied in the Y-axis. Here, the x-axis is time (in seconds), and the y-axis is force (in Newtons, N).

- **Selected Axis:**
  - Fy (blue line)

- **Key Statistics:**
  - Time Interval (Δt): 10.73500 seconds
  - Mean (μ): -1.026 N
  - Standard Deviation (σ): 0.030 N
  - Impulse (a): -11.018 Ns
  - Slope (s): -0.00 N/s (r²: 0.18)

### Observations

- The accelerations and forces are relatively constant over the observed time period, with small fluctuations.
- The statistical data provides mean values, indicating tendencies in movement and force throughout the measurement duration.
- The r² values suggest the linear fit's accuracy for slope measurements; close to zero indicates a negligible linear trend.

These graphs help in understanding the dynamics of the system under observation, offering key insights into movements and forces in specific directions.
Transcribed Image Text:## Data Analysis of Accelerometer and Force Measurements ### Accelerometer Graph The accelerometer readings are depicted in the first graph. It shows accelerations in three axes, but currently, the Ay (blue) and Az (green) axes are selected. The x-axis represents time (in seconds), and the y-axis shows acceleration (in m/s²). - **Selected Axes:** - Ay (blue line) - Az (green line) - **Key Statistics:** - Time Interval (Δt): 10.73500 seconds - **Ay:** - Mean (μ): -4.253 m/s² - Standard Deviation (σ): 0.015 m/s² - Acceleration (a): -45.654 m/s - Slope (s): 0.00 m/s³ (r²: 0.01) - **Az:** - Mean (μ): 8.795 m/s² - Standard Deviation (σ): 0.022 m/s² - Acceleration (a): 94.410 m/s - Slope (s): -0.00 m/s³ (r²: 0.00) ### Force Graph The second graph represents the force applied in the Y-axis. Here, the x-axis is time (in seconds), and the y-axis is force (in Newtons, N). - **Selected Axis:** - Fy (blue line) - **Key Statistics:** - Time Interval (Δt): 10.73500 seconds - Mean (μ): -1.026 N - Standard Deviation (σ): 0.030 N - Impulse (a): -11.018 Ns - Slope (s): -0.00 N/s (r²: 0.18) ### Observations - The accelerations and forces are relatively constant over the observed time period, with small fluctuations. - The statistical data provides mean values, indicating tendencies in movement and force throughout the measurement duration. - The r² values suggest the linear fit's accuracy for slope measurements; close to zero indicates a negligible linear trend. These graphs help in understanding the dynamics of the system under observation, offering key insights into movements and forces in specific directions.
The formula presented is:

\[
\sigma_C = \mu_C \sqrt{\left( \frac{\sigma_A}{\mu_A} \right)^2 + \left( \frac{\sigma_B}{\mu_B} \right)^2}
\]

This formula is typically used in the context of error propagation, specifically for the propagation of uncertainties in measurement. 

- \(\sigma_C\) represents the standard deviation or uncertainty of a calculated variable \(C\).
- \(\mu_C\) denotes the mean or average value of the calculated variable \(C\).
- \(\sigma_A\) and \(\sigma_B\) are the standard deviations or uncertainties of the variables \(A\) and \(B\), respectively.
- \(\mu_A\) and \(\mu_B\) are the mean values of the variables \(A\) and \(B\).

The formula calculates the uncertainty of the variable \(C\) by considering the uncertainties of the variables \(A\) and \(B\) using a square root of the sum of squares method.
Transcribed Image Text:The formula presented is: \[ \sigma_C = \mu_C \sqrt{\left( \frac{\sigma_A}{\mu_A} \right)^2 + \left( \frac{\sigma_B}{\mu_B} \right)^2} \] This formula is typically used in the context of error propagation, specifically for the propagation of uncertainties in measurement. - \(\sigma_C\) represents the standard deviation or uncertainty of a calculated variable \(C\). - \(\mu_C\) denotes the mean or average value of the calculated variable \(C\). - \(\sigma_A\) and \(\sigma_B\) are the standard deviations or uncertainties of the variables \(A\) and \(B\), respectively. - \(\mu_A\) and \(\mu_B\) are the mean values of the variables \(A\) and \(B\). The formula calculates the uncertainty of the variable \(C\) by considering the uncertainties of the variables \(A\) and \(B\) using a square root of the sum of squares method.
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