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The text only provides the question but does not include any answer options. The Jarque-Bera (JB) test statistic is calculated using the formula: JB = n × [(S²/6) + ((K-3)²/24)], where n is sample size, S is skewness, and K is kurtosis. Given: n = 100, S = 0.35, K = 3.04. Calculation: JB = 100 × [(0.35²/6) + ((3.04-3)²/24)] = 100 × [(0.1225/6) + (0.04²/24)] = 100 × [0.0204167 + (0.0016/24)] = 100 × [0.0204167 + 0.0000667] = 100 × 0.0204834 = 2.04834. The test statistic is approximately 2.05. At 95% confidence level with 2 degrees of freedom, the critical value from chi-square distribution is 5.991. Since 2.05 < 5.991, we fail to reject the null hypothesis of normality.
Author: Nikitesh Somanthe
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A financial analyst wishes to model the returns from investment using the normal distribution. The analyst approximates the skewness of the data to 0.35 and kurtosis of 3.04. The analyst performs the JB test at a 95% confidence level. What is the value of the test statistic as per the analyst's results if the sample size is 100?
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