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# Handling Multiple Score Parameters in Batoi Insight

In survey analysis, it's common to encounter scenarios where multiple score parameters need to be considered for a single group of questions. Batoi Insight provides mechanisms to handle these complexities through weighted and combined operations on score parameters. This section explains handling and computing values when multiple score parameters are involved.

### Concept of Multiple Score Parameters

#### Score Parameters (S-Parameters):

Score parameters assign quantitative values to survey responses, which can be used to measure and compare results. These parameters can include a set of labels, values, colors, and types (progressive, regressive, neutral).

#### Multiple Score Parameters:

When a group of questions or responses has more than one score parameter, we must combine these parameters meaningfully to obtain a single, interpretable score.

### Intra-Group Statistical Operations

To combine multiple score parameters for a group, we use a weighted combination of the statistical tendencies of each parameter. The general formula is:

where

• π(π) is the weight of the π-th score parameter.
• ST(Si(j)) is the statistical tendency (mean, median, mode) of the j-th score parameter for the i-th question.
• [ππππππ‘πππ] can be + (addition), β (subtraction), . (multiplication), or / (division).

### Step-by-Step Process

#### Step 1: Define Score Parameters and Weights

• Identify all score parameters associated with each question or group.
• Assign weights to each score parameter based on their importance.

#### Example:

For a question with two score parameters Si(1) and Si(2):

• Score Parameter 1: Satisfaction Score (0 to 5 scale)
• Score Parameter 2: Importance Score (1 to 3 scale)
• Weights: W(1) = 0. 6 and W(2) = 0. 4

#### Step 2: Calculate Statistical Tendencies

• Compute the statistical tendency (e.g., mean) for each score parameter.

#### Example:

Assume we have the following scores for a question:

• Satisfaction Scores: [4, 5, 3, 4]
• Importance Scores: [2, 3, 1, 2]

Calculate the mean for each score parameter:

#### Step 3: Apply Weights and Combine Scores

• Use the weights and operations to combine the statistical tendencies of the score parameters.

#### Example:

Combine the mean scores using addition:

#### Step 4: Normalize the Combined Score (if necessary)

Normalize the combined score to a standard scale (e.g., 0-1, 0-100) if required.

#### Example:

Normalize to a 0-1 scale (assuming the original scale is 0-5):

### Practical Implementation

The following is a step-by-step example:

1. Define Scores and Weights:

• Satisfaction Scores: [4, 5, 3, 4]
• Importance Scores: [2, 3, 1, 2]
• Weights: W(1) = 0. 6, W(2) = 0. 4

2. Calculate Statistical Tendencies:

• Mean Satisfaction Score: 4
• Mean Importance Score: 2

3. Combine Scores:

ST(Si)= 0.6 β 4 + 0.4 β 2 = 3.2

4. Normalize (if necessary):

• Normalized Score: 0.64

### Handling Complex Scenarios

Sometimes, we might need to apply different operations between score parameters. For instance, add some parameters and multiply others.

### Conclusion

Handling multiple score parameters in Batoi Insight involves defining weights, calculating statistical tendencies, combining scores using specified operations, and normalizing the result if necessary. Following these steps, we can effectively analyze and interpret complex survey data, gaining valuable insights from multiple dimensions.

Please refer to our documentation or contact support for further assistance or detailed examples.