Read the question carefully. The actual change consists of exactly 4 coins, and each coin must be either 1, 5, 10, or 25 cents. The goal is to determine the total value.
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Statement (1): One of the coins is a 1-cent coin.
The remaining three coins can still be any allowed denominations, leading to many possible totals. Therefore, statement (1) alone is insufficient.
Statement (2): The same total value can also be made using exactly 2 coins.
Do not think about specific 4-coin combinations yet. Instead, think about possible totals that have both a 2-coin representation and a 4-coin representation. For example, 20 can be made as 10 + 10 or as 5 + 5 + 5 + 5. Likewise, 30 can be made as 25 + 5 or as 10 + 10 + 5 + 5. Since multiple totals satisfy this condition, statement (2) alone is insufficient.
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Now combine both statements.
From statement (1), the actual 4-coin combination contains a 1-cent coin. Therefore, its total cannot be a multiple of 5, because adding a single 1-cent coin to the remaining coins (which are all multiples of 5) produces a total ending in 1 or 6, not 0 or 5.
Hence, in the 2-coin representation from statement (2), one of the two coins must also be a 1-cent coin. The possible 2-coin totals are 1 + 1 = 2, 1 + 5 = 6, 1 + 10 = 11, and 1 + 25 = 26.
Now check which of these can also be formed using exactly 4 allowed coins. Total 2, 6, and 11 cannot be made with exactly 4 coins. However, 26 can be made as 10 + 10 + 5 + 1.
Since only one total survives, the answer is C.
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Transferable learning:
Whenever a Data Sufficiency question says the same value can be represented in different ways, avoid generating random combinations. First, identify every possible representation implied by one statement. Then use the second statement to eliminate possibilities. If only one value remains, the statements together are sufficient. This approach is much faster and more reliable than brute-forcing coin combinations.